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5 Analytics Tools for Tracking and Measurement
 
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You would need these five essential analytics tools in your tracking stack to be successful with taking your data to the next level. Mentioned Tools: Google Analytics - https://analytics.google.com Google Tag Manager - https://www.google.com/analytics/tag-manager/ Adobe Analytics - http://www.adobe.com/marketing-cloud/web-analytics.html Adobe DTM - https://dtm.adobe.com/sign_in Kiss Metrics - https://www.kissmetrics.com/ Mixpanel - https://mixpanel.com/ R Language - https://www.r-project.org/about.html SurveyMonkey - https://www.surveymonkey.com/ SurveyGizmo - https://www.surveygizmo.com/ Tableau - http://www.tableau.com/ Optimizely - https://www.optimizely.com/ Drip - https://www.drip.co/ Free GTM GTM Beginner course: https://gtmtraining.com/emailcourse Course: http://gtmtraining.com/products Learn more about measurement: http://measureschool.com Follow us…. https://twitter.com/measureschool https://www.facebook.com/measureschool . . RECOMMENDED MEASURE BOOKS: https://kit.com/Measureschool/recommended-measure-books GEAR WE USED TO PRODUCE THIS VIDEO: https://kit.com/Measureschool/measureschool-youtube-gear
Views: 46844 Measureschool
Big Data Tools and Technologies | Big Data Tools Tutorial | Big Data Training | Simplilearn
 
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This Big Data Tools Tutorial will explain what is Big Data?, Big Data challenges and some of the popular Big Data tools involed in Big Data processing and management. The main challenge of Big Data is storing and processing the data at a specified time span. The traditional approach is not efficient in doing that. So Hadoop technologies and various Big Data tools have emerged to solve the challenges in Big Data environment. There are a lot of Big Data tools, all of them help in some or the other way in saving time, money and in covering business insights. This video will talk about such tools used in Big Data management. Subscribe to Simplilearn channel for more Big Data and Hadoop Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Check our Big Data Training Video Playlist: https://www.youtube.com/playlist?list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ Big Data and Analytics Articles - https://www.simplilearn.com/resources/big-data-and-analytics?utm_campaign=BigData-Tools-Tutorial-Pyo4RWtxsQM&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Big Data and Hadoop, check our Big Data Hadoop and Spark Developer Certification Training Course: https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=BigData-Tools-Tutorial-Pyo4RWtxsQM&utm_medium=Tutorials&utm_source=youtube #bigdata #bigdatatutorialforbeginners #bigdataanalytics #bigdatahadooptutorialforbeginners #bigdatacertification #HadoopTutorial - - - - - - - - - About Simplilearn's Big Data and Hadoop Certification Training Course: The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. You will also learn the various interactive algorithm in Spark and use Spark SQL for creating, transforming, and querying data form. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-commerce. This Big Data course also prepares you for the Cloudera CCA175 certification. - - - - - - - - What are the course objectives of this Big Data and Hadoop Certification Training Course? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames - - - - - - - - - - - Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists - - - - - - - - For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 16887 Simplilearn
Overview of Analytics: Companies in Analytics and Popular Analytics Tools
 
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Jigsaw Academy presents a video on companies in analytics and various tools used in analytics. Jigsaw Academy is an award winning premier online analytics training institute that aims to meet the growing demand for talent in the field of analytics by providing industry-relevant training to develop business-ready professionals.Jigsaw Academy has been acknowledged by blue chip companies for quality training Follow us on: https://www.facebook.com/jigsawacademy https://twitter.com/jigsawacademy http://jigsawacademy.com/
Views: 15856 Jigsaw Academy
Big Data Analytics | Big Data Explained | Big Data Tools & Trends | Big Data Training | Edureka
 
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** Big Data Hadoop Training: https://www.edureka.co/big-data-and-hadoop ** This Edureka Big Data Analytics video will help you in understanding what is Big Data Analytics & how it is revolutionizing various domains. Below are the topics covered in this Big Data Analytics video: 1) Why Big Data Analytics? 2) What is Big DataAnalytics? 3) Different Stages in Big Data Analytics 4) Different Types of Big Data Analytics 5) Tools used in Big Data Analytics 6) Big Data Analytics in Different Domains 7) Trends in Big Data Analytics Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Hadoop playlist here: https://goo.gl/hzUO0m - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 40 hours of assignment and 30 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka’s Big Data and Hadoop online training is designed to help you become a top Hadoop developer. During this course, our expert Hadoop instructors will help you: 1. Master the concepts of HDFS and MapReduce framework 2. Understand Hadoop 2.x Architecture 3. Setup Hadoop Cluster and write Complex MapReduce programs 4. Learn data loading techniques using Sqoop and Flume 5. Perform data analytics using Pig, Hive and YARN 6. Implement HBase and MapReduce integration 7. Implement Advanced Usage and Indexing 8. Schedule jobs using Oozie 9. Implement best practices for Hadoop development 10. Work on a real life Project on Big Data Analytics 11. Understand Spark and its Ecosystem 12. Learn how to work in RDD in Spark - - - - - - - - - - - - - - Who should go for this course? If you belong to any of the following groups, knowledge of Big Data and Hadoop is crucial for you if you want to progress in your career: 1. Analytics professionals 2. BI /ETL/DW professionals 3. Project managers 4. Testing professionals 5. Mainframe professionals 6. Software developers and architects 7. Recent graduates passionate about building successful career in Big Data - - - - - - - - - - - - - - Why Learn Hadoop? Big Data! A Worldwide Problem? According to Wikipedia, "Big data is collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications." In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, it is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success! The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop has become an integral part for storing, handling, evaluating and retrieving hundreds of terabytes, and even petabytes of data. - - - - - - - - - - - - - - Opportunities for Hadoopers! Opportunities for Hadoopers are infinite - from a Hadoop Developer, to a Hadoop Tester or a Hadoop Architect, and so on. If cracking and managing BIG Data is your passion in life, then think no more and Join Edureka's Hadoop Online course and carve a niche for yourself! For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review: Michael Harkins, System Architect, Hortonworks says: “The courses are top rate. The best part is live instruction, with playback. But my favourite feature is viewing a previous class. Also, they are always there to answer questions, and prompt when you open an issue if you are having any trouble. Added bonus ~ you get lifetime access to the course you took!!! ~ This is the killer education app... I've take two courses, and I'm taking two more.”
Views: 18463 edureka!
Choosing which statistical test to use - statistics help.
 
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Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties. There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.
Views: 803931 Dr Nic's Maths and Stats
Top 4 Data Analytics Tools
 
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TOP 4 DATA ANALYTICS TOOLS //Data analytics tools are key for any data analyst or data scientist to know. Which tool should you learn though? I’ll go through several options and the advantages of learning each one for your career in data. From Python to R and SAS, find out which analysis tool will suit you best. These recommendations are based on 2 main criteria: Availability / Job Scenario Ease of learning __________ ✅ Build The Perfect Resume to land your next analytics job: http://bit.ly/TCFPerfectResume 💯 Achieve your career goals with personal career guidance from me: http://bit.ly/TCFCoaching __________ Are you ready to take the next steps in your career and want the best career advice? Let The Career Force be your guide. 📃 Download my FREE guide - LAND YOUR NEXT JOB here: http://bit.ly/TCFguide __________ CONNECT WITH ME: Website: https://thecareerforce.com Linked In: https://www.linkedin.com/company/the-career-force/ Facebook: https://www.facebook.com/TheCareerForce Instagram: http://instagram.com/thecareerforce https://youtu.be/OBvZhFVesvI
Views: 1481 The Career Force
Predictive Analytics Process & Tools
 
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Introduction to predictive analytics. Overview of the process, opportunities, challenges and free tools available. Link to post: http://storybydata.com/predictive-analytics-101/
Views: 8794 Story by Data
Top Data Analyst Skills | Data Analyst Career Insights | UpGrad
 
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Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyze behavioural data and patterns, and techniques vary according to organizational requirements. With the advent of the digital revolution, analytics is sweeping across industries in a huge way. Mastering certain data analytics skills can enable you to chart a successful career in this lucrative and rapidly changing domain. Data analytics is bringing about changes in the ways you navigate to work every day or the cabs you hail through your phone, or the mobile applications to deliver food at your doorsteps, to the online shopping you find yourself doing on weekends. All of this activity generates massive amounts of data. This is where companies who have created these products come in. Analytics is changing the way we also do business. Deriving insights from large volumes of data to enable better decision-making and even better customer experience has become the norm for competitive firms these days. Which is why being a data analyst in this world pays off well. Through this UpGrad Careers-In-Shorts Series, Rohit Sharma, Program Director at UpGrad, takes you through all you need to know about data analytics - the most promising career of tomorrow! The first one here is about the 4 core skills that will help you transition to the field of data analytics - a career of the future. Want to Be a Data Analyst? Here are Top Skills & Tools to Master: https://blog.upgrad.com/want-to-be-a-data-analyst-here-are-top-skills-tools-to-master/?utm_source=YouTube&utm_medium=Organic_Social&utm_campaign=YouTube_Video&utm_term=YouTube_Video_Data&utm_content=YouTube_Video_Data_Analytics_Skills_Blog_Link Transition to one of the coolest jobs in the industry. Enrol now to be an expert Data Analyst: https://upgrad.com/data-science/?utm_... #CareerswithUpGrad #DataAnalytics #DigitalCareers upGrad is an online higher education platform providing rigorous industry-relevant programs designed and delivered in collaboration with world-class faculty and industry. Merging the latest technology, pedagogy, and services, upGrad is creating an immersive learning experience – anytime and anywhere. upGrad began in 2015 with the conviction that in an ever-changing industry, professionals need to continuously upskill themselves in order to stay relevant. upGrad has created some of India’s largest online programs to help thousands of professionals achieve their career goals in the areas of data, technology, and management. Stay on top of your industry by interacting with us on our social channels: Follow us on Instagram: https://instagram.com/upgrad_edu Like us on Facebook: https://www.facebook.com/UpGradGlobal Follow us on Twitter: https://www.twitter.com/upgrad_edu Follow us on LinkedIn: https://www.linkedin.com/company/ueducation/Joint Certificate from Cambridge Judge Business School Executive Education and upGrad‌
Views: 57429 upGrad
Learn Basic statistics for Business Analytics
 
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Business Analytics and Data Science are almost same concept. For both we need to learn Statistics. In this video I tried to create value on most used statistical methods for Data Science or Business Analytics for Statistical model Building. Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. In applying statistics any can handle a scientific, industrial, or societal problem. I value your time and effort that is why I have capture almost 20 statically concept in this video. Learn Basic statistics for Business Analytics Here I have capture how to learn Mean, how to learn Mode, How to learn median, Concept of Sleekness, Concept of Kurtosis, learn Variables, concept of Standard deviation, Concept of Covariance, Concept of correlation, Concept of regression, How to read regression formula, how to read regression graph, Concept of Intercept, Concept of slope coefficient, Concept of Random Error, Different types of regression Analysis, Concept ANOVA (Analysis of Variance), How to read ANOVA table, How to learn R square (Interpreted R square), Concept of Adjusted R Square, Concept of F test, Concept of Information Value, Concept of WOE, Concept of Variable inflation Factors. Learn Basic statistics for Business Analytics By this video you can Start Learn statistics for Data Science and Business analytics easily and effectively. These statistics are useful when at the time of running linear regression, Logistic regression statistics models. For Statistical Data Exploration you may need to see Meager of central tendency and Data Spread in Statistics. By Understanding Mean, Mode, Median, Sleekness, Kurtosis, Variance, Standard deviation. Learn Basic statistics for Business Analytics To understand statistical relationship between variables you can use Covariance, Correlation coefficient, Regression , ANOVA (Analysis of Variance) . Learn Basic statistics for Business Analytics To understand Strength of stastical relationship between variables you can use R square, Adjusted R square, F test. If you want to understand variable importance in your stastical model you can use Information value (IV) and Weight of evidence (WOE) Concept. Information value and Weight of evidence mostly used in Logistic Regression Analysis. Learn Basic statistics for Business Analytics Variable inflation factors (VIF) is used for understanding, It is the stastical method to understand variable importance. What is the importance of this variable statically in the Regression model? By VIF we check Correlation between variable. Learn Basic statistics for Business Analytics At last I have explained when to use ANOVA, When to Use Linear regression and when to use Logistic regression. Learn Basic statistics for Business Analytics Thank you So much for watching this video, Hope I can add some value in your Journey as a Statistician, Business Analytics professional and Data Scientist professional. Blogger : http://koustav.analyticsanalysis.busi... google plus: https://plus.google.com/u/0/115750715 facebook link: https://www.facebook.com/koustav.biswas.31945?ref=bookmarks website: https://www.analyticsanalysisbusiness.com
Circuit Tools data analysis tutorial
 
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A tutorial comparing two different drivers and showing how to analyse the data to help the slower driver. Circuit Tools is used to analyse data from the Racelogic Video VBOX.
Views: 3811 VBOX Motorsport
Digital Analytics Fundamentals | Web Analytics For Beginners | Digital Marketing | Simplilearn
 
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This Digital Analytics Fundamentals Tutorial will give an introduction to Digital Analytics, introduction to Data Analytics followed by some real life examples. Digital Analytics is the science of analysis that focuses on Internet data. It involves the collection, analysis, and data-informed decisions leading to the optimization of an organization's digital ecosystem and supporting business processes. Data from websites, mobile applications, social media, Internet of Things, or third party sources are commonly combined with back-office Customer Relationship Management (CRM) and Sales systems to inform business decisions. Digital Analytics has become an integral part of core business strategies, workflow optimization, and maintaining a competitive edge. This Digital Analytics Tutorial will explain the topics listed below: -( 00:14 ) Introduction to Digital Analytics -( 01:31 ) Introduction to Data Analytics -( 02:04 ) Understanding the 10/90 Rule -( 03:30 ) Understanding 20/80 Rule -( 08:48 ) Digital Analytics Continuous Improvement Process and Methodology -( 15:18 ) Tools, Technology, and Data Integration -( 17:23 ) Digital Analytics Real-life Example #DigitalMarketing #SimplilearnDigitalMarketing #DigitalMarketingCourse #DigitalMarketingCertification #DigitalMarketingCertifiedAssociate Subscribe to Simplilearn channel for more Social Media Marketing Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 For More Digital Marketing Tutorial videos, check our Digital Marketing tutorial for beginners playlist: https://www.youtube.com/watch?v=xA_yMYN19ug&list=PLEiEAq2VkUULa5aOQmO_al2VVmhC-eqeI Digital Marketing Articles: https://www.simplilearn.com/resources/digital-marketing?utm_campaign=Digital-Analytics-Fundamentals-WaDjcajOmUo&utm_medium=Tutorials&utm_source=youtube To Gain in-depth knowledge of Digital Analytics and other Digital Marketing concepts, check out Advanced Web Analytics Course: https://www.simplilearn.com/digital-marketing/web-analytics-certification-training?utm_campaign=Digital-Analytics-Fundamentals-WaDjcajOmUo&utm_medium=Tutorials&utm_source=youtube ------------------------------------- What’s the focus of this Advanced Web Analytics course? Advanced Web Analytics is the science of analysis that focuses on Internet data. It involves the collection, analysis, and data-informed decisions leading to the optimization of an organization's digital ecosystem and supporting business processes. Data from websites, mobile applications, social media, Internet of Things, or third party sources are commonly combined with back-office Customer Relationship Management (CRM) and Sales systems to inform business decisions. Web Analytics has become an integral part of core business strategies, workflow optimization, and maintaining a competitive edge. This Web Analytics course covers fundamental concepts of analytics and deep dives into web, social, content and mobile analytics common scenarios and covers the popular web analytics tools used by marketers across the major industry domains. Although this course approaches on learning Digital Analytics from a managerial perspective, it will showcase tips and techniques for the most common google web analytics platform and several other relevant tools along the way. -------------------------------------- What are the course objectives of this Advanced Web Analytics Course? Advanced Web Analytics training gives participants well-rounded knowledge in digital data analytics, including: 1. How to leverage data from various sources to conduct quantitative and qualitative research, and deliver actionable, data-informed business insights 2. How digital data analytics drives important insights for all aspects of your customer’s life cycle across the entire digital world 3. Uncover and learn about the various analysis capabilities enabled through digital data 4. How to better inform business decisions with rigorous analysis techniques ---------------------------------------- Who should take this course? This Digital Analytics training module is suitable for professionals who want to learn and specialize in digital analytics to boost their skillsets in the digital marketing industry and beyond. This course is best suited for participants who are: 1. Online Web Analytics Implementers 2. Online Web Analytics Data Reporters 3. Digital Analysts 4. Digital Marketers 5. Managers 6. Web Analytics Certification Aspirants 7. Digital Analytics Certification Aspirants ---------------------------------------- For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0"
Views: 12384 Simplilearn
Tools Used in Data Visualization ll Data Analytics ll Explained in Hindi
 
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📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Discrete Mathematics (DM) Theory Of Computation (TOC) Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 7491 5 Minutes Engineering
MATLAB Tools for Scientists: Introduction to Statistical Analysis
 
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Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe ------------------------------------------------------------------------- Researchers and scientists have to commonly process, visualize and analyze large amounts of data to extract patterns, identify trends and relationships between variables, prove hypothesis, etc. A variety of statistical techniques are used in this data mining and analysis process. Using a realistic data from a clinical study, we will provide an overview of the statistical analysis and visualization capabilities in the MATLAB product family. Highlights include: • Data management and organization • Data filtering and visualization • Descriptive statistics • Hypothesis testing and ANOVA • Regression analysis
Views: 20410 MATLAB
Data Analysis in Excel Tutorial
 
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Data Analysis using Microsoft Excel using SUMIF , CHOOSE and DATE Functions
Views: 122858 TEKNISHA
Data analysis tools used in Ethnobotanical study
 
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some important ethnobotanical data analysis tools which are mostly used are given in this video such as ICF
Business Analytics with Excel | Data Science Tutorial | Simplilearn
 
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Business Analytics with excel training has been designed to help initiate you to the world of analytics. For this we use the most commonly used analytics tool i.e. Microsoft Excel. The training will equip you with all the concepts and hard skills required to kick start your analytics career. If you already have some experience in the IT or any core industry, this course will quickly teach you how to understand data and take data driven decisions relative to your domain using Microsoft excel. Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Data-Excel-W3vrMSah3rc&utm_medium=SC&utm_source=youtube For a new-comer to the analytics field, this course provides the best required foundation. The training also delves into statistical concepts which are important to derive the best insights from available data and to present the same using executive level dashboards. Finally we introduce Power BI, which is the latest and the best tool provided by Microsoft for analytics and data visualization. What are the course objectives? This course will enable you to: 1. Gain a foundational understanding of business analytics 2. Install R, R-studio, and workspace setup. You will also learn about the various R packages 3. Master the R programming and understand how various statements are executed in R 4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R 5. Define, understand and use the various apply functions and DPLYP functions 6. Understand and use the various graphics in R for data visualization 7. Gain a basic understanding of the various statistical concepts 8. Understand and use hypothesis testing method to drive business decisions 9. Understand and use linear, non-linear regression models, and classification techniques for data analysis 10. Learn and use the various association rules and Apriori algorithm 11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: IT professionals looking for a career switch into data science and analytics Software developers looking for a career switch into data science and analytics Professionals working in data and business analytics Graduates looking to build a career in analytics and data science Anyone with a genuine interest in the data science field Experienced professionals who would like to harness data science in their fields Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 44561 Simplilearn
Microsoft Excel data analysis tool for statistics mean, median, hypothesis, regression
 
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This video covers a few topics using the data analysis tool. After this video you should be able to: a) Find and use data analysis on excel to calculate statistics b) Calculate the mean, median, mode, standard deviation, range and coefficient variation on a variable set of data in excel. c) Conduct a confidence interval in excel. d) Complete a T-test in excel to help complete a hypothesis test. e) Conduct a linear regression analysis output from excel and create a scatter diagram.
Views: 113925 Me ee
Top 5 Analytics Tools 2018. Adobe Analytics
 
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5 leading tools for Data Analytics, Web Analytics, Big Data Analysis, Social Media Analytics, Predictive Analysis, Business Analysis, Mobile apps — all in one cloud. ▶ Adobe Mobile Services — analytics tool for mobile apps that also includes acquisition link tracking, deep links, messaging and geo-targeting. ▶ Adobe Analytics Report Builder — an Excel plug-in to query analytics data in real-time. Ideal for those who used to work in Microsoft Excel. ▶ Reports and Analytics — web analytics for beginners. ▶ Ad Hoc Analysis — analytics tool for advanced analysts with unlimited real-time segmentation options. For those who spend most of their time analysing the data and looking for insights. ▶ Analysis Workspace — #1 data analytics tools for all type of users. 🎓 Individual Trainings on Adobe Analytics https://training.osadchuka.com 📌 SUBSCRIBE https://www.youtube.com/channel/UCq8K5VisTEpzz9aCEHlsz2Q?sub_confirmation=1 - - - - - - - - - - - - WATCH OTHER VIDEOS - - - - - - - - - - - - 🎥 Adobe Analytics vs Google Analytics https://youtu.be/QsiuTFsW4e0 🎥 Analysis Workspace Tutorials https://www.youtube.com/watch?v=UhAx8rHUrCY&list=PLdHxf9so_4cwoWOpjjCXs9fwifUhk5Syp 🎥 Bitcoin Analysis in Adobe Analytics https://youtu.be/jO1pZJwbjpM 🎥 Actual vs Target Analysis https://youtu.be/6HpBbVyzG8M - - - - - - - - - - - - USEFUL LINKS - - - - - - - - - - - - - - - - - - 🔗 Adobe Mobile Services https://marketing.adobe.com/resources/help/en_US/mobile/usage_overview.html 🔗 Report Builder https://www.adobe.com/data-analytics-cloud/analytics/report-builder.html 🔗 Reports and Analytics https://marketing.adobe.com/resources/help/en_US/sc/user/t_running_report.html 🔗 Ad Hoc Analysis https://www.adobe.com/data-analytics-cloud/analytics/ad-hoc-analysis.html - - - - - - - - - - - - LET’S GET CONNECTED - - - - - - - - - - - - 📷 Instagram https://www.instagram.com/adobeanalytics_pro/ 👤 LinkedIn https://linkedin.com/in/andreyosadchuk #AdobeAnalytics #WebAnalytics #Analytics #AnalyticsTraining #WebAnalyticsTraining
Views: 2486 Andrey Osadchuk
Types of Research Tools: Super Easy Explanation (UGC NET Paper 1)
 
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This video will brief you about all research tools and techniques which is an important area from which questions are asked in UGC NET Exam. But why is it important? Let's imagine that you have just enrolled in your first college course. After two days of class, your professor assigns you a research assignment. You are to research which type of school system is better, private or public. Immediately, you have an opinion of which system you feel is better, but you realize that conducting research is not about your own personal opinion. Research is about gathering data that you can analyze and use to come to some sort of conclusion. So, before you begin your data collection, you realize that you have a lot to learn about the various methods and techniques of gathering data. A properly run experiment depends on using the right tools, both for data collection and analysis. In the end, it will save you time, money and frustration to spend some time planning out which tools are most appropriate for your work. Struggling to find NTA UGC NET/JRF English coaching near your home? Join India's finest online coaching for NTA UGC NET/JRF English Literature only at https://www.arpitakarwa.com/ Our NTA UGC NET English Online Course includes 800 Audios, 200 PDFs, 300 Mock Tests. The Course also covers all states SET/SLET syllabus. NTA UGC NET English Online Course Details: https://bit.ly/2GOA6J4 NTA UGC NET Course Video (10 Minutes) https://bit.ly/2wGZc9w NTA UGC NET Detailed Course Syllabus: https://bit.ly/2WVRRi4 Quick Revision PDFs on Most Important Topics: http://bit.ly/2HaUp6N Mock Test Series for NTA UGC NET English: https://bit.ly/2C85Jjy Demo Audios & PDFs: https://bit.ly/2wol3Tg Result of our Students: https://bit.ly/2LFwkJc Arpita’s Educational Qualification: https://bit.ly/2UJSLkb Solved Previous Year Papers of NTA UGC NET: https://bit.ly/2U5OrYe Follow us to receive GoNETQuiz & latest UGC NET updates: Whatsapp: 7976603731 Facebook: https://www.facebook.com/arpitakarwa.ugcnet/ Instagram: https://www.instagram.com/arpitakarwa.ugcnet/ YouTube: https://www.youtube.com/arpitakarwa/ Telegram: http://www.t.me/arpitakarwa #ResearchTools #DetailedCourse #Paper1
Views: 33367 Arpita Karwa
Business Data Analysis with Excel
 
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Lecture Starts at: 8:25 Business data presents a challenge for the data analyst. Business data is often aggregated, recorded over time, and tends to exhibit autocorrelation. Additionally, and most problematically, the amount of business data is usually quite limited. These characteristics lead to a situation where many of the tools in the analyst's tool belt (e.g., regression) aren't ideal for the task. Despite these challenges, proper analysis of business data represents a fundamental skill required of Business/Data Analysts, Product/Program Managers, and Data Scientists. At this meetup presenter Dave Langer will show how to get started analyzing business data in a robust way using Excel – no programming or statistics required! Dave will cover the following during the presentation: • The types of business data and why business data is a unique analytical challenge. • Requirements for robust business data analysis. • Using histograms, running records, and process behavior charts to analyze business data. • The rules of trend analysis. • How to properly compare business data across time, organizations, geographies, etc.Where you can learn more about the tools and techniques. *Excel spreadsheets can be found here: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Business%20Data%20Analysis%20with%20Excel **Find out more about David here: https://www.meetup.com/data-science-dojo/events/236198327/ -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz7sf0 Watch the latest video tutorials here: https://hubs.ly/H0hz8rL0 See what our past attendees are saying here: https://hubs.ly/H0hz7ts0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 52748 Data Science Dojo
Microsoft Power Tools for Data Analysis: Dashboards & Reports. Class Introduction Video. MSPTDA #01.
 
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Download Excel File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/Intro/001-MSPTDA-IntroToClass.xlsx Download pdf Notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/Intro/001-MSPTDA-IntroToClass.pdf This video introduces the topics that will be covered in this Highline College BI 348 Class: Name of Class: BI 348 – Microsoft Power Tools for Data Analysis: • Power Query • Power Pivot • DAX • Power BI Desktop • Excel For Creating: • Data Models, Reports, Dashboards and Analytics Taught by Mike excelisfun Girvin, Excel MVP 2013-2018 • A class about connecting to multiple source of data, transforming the data into a refreshable & dynamic data model, and building reports and dashboards to provide insightful and actionable information. Prerequisites for this class: • Busn 216: Excel Basics, https://www.youtube.com/playlist?list=PLrRPvpgDmw0n34OMHeS94epMaX_Y8Tu1k • Busn 218: Advanced Excel, https://www.youtube.com/playlist?list=PLrRPvpgDmw0lcTfXZV1AYEkeslJJcWNKw • Busn 210: Business Statistics, https://www.youtube.com/playlist?list=PLrRPvpgDmw0ngx_uPhvasTbOWLOztsaBj What Version of Excel: • Office 365 (updated each month) What Version of Power BI Desktop: • Free Tool we will download (update each month) Over View of Topics for the class: 1. Data Analysis / Business Intelligence terms and concepts that we will learn in this class: • Proper Data Set • Fact Table • Dimension Tables • Relationships • Star Schema • ETL • Measures • Dashboards • SQL • Data Warehousing   2. Learn how to use Excel Power Query: • Import Data from multiple sources • Clean and Transform Data • Create Data Components for Star Schema Data Models • Load Data To Excel, the Data Model and Connection Only • Replace Complicated Excel Solutions with Power Query Solution • Use the Power query User Interface to create Power Query Solutions • Learn about the Case Sensitive, Function-based M Code Language that is behind the scenes in Power Query 3. Learn how to use Excel Power Pivot: • Excel Power Pivot provides: i. Data Model where we can have multiple tables, formulas and relationships (Star Schema) ii. Columnar Database to hold "Big Data" and process quickly over that "Big Data" iii. New Formula Language called DAX: 1. Many More Calculations than in Standard PivotTable 2. Build One Formula that can work in many reports 3. Add Number Formatting to Formulas • Excel Power Pivot to: i. Replace VLOOKUP Formulas and Single Flat PivotTable Data Source with Multiple Tables, Relationships in the Data Model to create more efficient Reports & Dashboards ii. Use Power Pivot Columnar Database to hold millions of rows of data iii. DAX formulas have more Power than Standard PivotTable Calculations 4. Learn about Building Star Schema Data Models: a. Why they are important in Power Pivot and Power BI Desktop b. How to build them using: i. Power Query ii. Power Pivot iii. DAX iv. Power BI Desktop 5. Learn how to author DAX Formulas for Excel’s Power Pivot & Power BI Desktop: a. Calculated Column Formulas for Data Model b. Measure Formulas for PivotTables c. DAX Functions like SUMX, CALCULATE, RELATED, and Much More… d. Lean why we must create Explicit rather than Implicit formulas e. Learn how Row Context works in formulas f. Learn how Filter Context works in formulas g. Learn about Scalar & Table Functions h. Use DAX Studio to visualize and analyze DAX Formulas 6. Learn how to use Power BI Desktop: a. Power Query to import, clean, transform and create Star Schema Data Models b. Create Relationships c. Create DAX Formulas d. Build Interactive Visualizations e. Build Dashboards   7. Learn how to use Excel: • Spreadsheet Formulas & Functions • Standard PivotTables • Power Query • Power Pivot • Build Data Model PivotTables and the resultant Reports, Dashboards and Analytics 8. Building Refreshable, Insightful Dashboards a. Build Excel Dashboards b. Build Power BI Dashboards 9. Case Studies to practice using Power Pivot & Power BI Desktop for Reporting, Building Dashboards and Building Business Analytics Solutions The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 37616 ExcelIsFun
Data Analysis in SPSS Made Easy
 
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Use simple data analysis techniques in SPSS to analyze survey questions.
Views: 868978 Claus Ebster
Data Science In 5 Minutes | Data Science For Beginners | What Is Data Science? | Simplilearn
 
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This Data Science tutorial video will give you an idea on the life of a Data Scientist, steps involved in Data science project, roles & salary offered to a Data Scientist. Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and analysis. In simple terms, it is the umbrella of techniques used when trying to extract insights and information from data. Now, let us get started and understand what is Data Science all about. Below topics are explained in this Data Science tutorial: 1. Life of a Data Scientist 2. Steps in Data Science project - Understanding the business problem - Data acquisition - Data preparation - Exploratory data analysis - Data modeling - Visualization and communication - Deploy & maintenance 3. Roles offered to a Data Scientist 4. Salary of a Data Scientist To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-X3paOmcrTjQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 374621 Simplilearn
Which tools are commonly used for Data Analysis?
 
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"Which tools are commonly used for Data Analysis" this is a very common question. In this video I share my my point of view based on my experience.
▶ 5 Most Used Data Mining Software || Data Mining Tools -- Famous Data Mining Tools
 
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»See Full #Data_Mining Video Series Here: https://www.youtube.com/watch?v=t8lSMGW5eT0&list=PL9qn9k4eqGKRRn1uBmEhlmEd58ATOziA1 In This Video You are gonna learn Data Mining #Bangla_Tutorial Data mining is an important process to discover knowledge about your customer behavior towards your business offerings. » My #Linkedin_Profile: https://www.linkedin.com/in/rafayet13 » Read My Full Article on Data Mining Career Opportunity & So On » Link: https://medium.com/@rafayet13 #Learn_Data_Mining_In_A_Easy_Way #Data_Mining_Essential_Course #Data_Mining_Course_For_Beginner Here We're Going to Learn Which Software is best to use in Data Mining Field R remains the leading tool, with 49% share, but Python grows faster and almost catches up to R. RapidMiner remains the most popular general Data Science. আধুনিক প্রযুক্তির ব্যবহার বৃদ্ধির সাথে অতি দ্রুত ডেটা উৎপন্ন হচ্ছে। টেক জায়ান্ট আইবিএম জানায় ইন্টারনেটে যত ডেটা আছে তার ৯০ ভাগ উৎপন্ন হয়েছে গত তিন বছরে। এ ডেটা উৎপন্নের হার দিনকে দিন বেড়েই চলছে। বিশেষজ্ঞদের ধারনা ২০২০ সাল নাগাদ প্রায় ৪০ জেটাবাইট ডেটা জেনারেট হবে। যা ২০১১ তুলনায় প্রায় ৫০ গুন বেশি। বিশাল পরিমাণ এই ডেটা প্রক্রিয়াজাতের মাধ্যমে বিজ্ঞান, গবেষণা, চিকিৎসা, শিক্ষা ও ব্যবসায় ব্যপক ভুমিকা রাখা যেতে পারে। তাই বলা হচ্ছে “ বিগ ডেটা ইজ বিগ ইমপ্যাক্ট।” Data Mining,big data,data analysis,data mining tutorial,book , Bangla tutorials,data mining software,Data Mining,What is data mining, bookbd, data analysis,data mining tutorial,data science,big data,business tutorial,data mining Bangla tutorial,how to,how to mine data,knowledge discovery,Artificial Intelligence,Deep learning,machine learning,Python tutorials,
Views: 7756 BookBd
Qualitative analysis of interview data: A step-by-step guide
 
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The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends. The steps are also described in writing below (Click Show more): STEP 1, reading the transcripts 1.1. Browse through all transcripts, as a whole. 1.2. Make notes about your impressions. 1.3. Read the transcripts again, one by one. 1.4. Read very carefully, line by line. STEP 2, labeling relevant pieces 2.1. Label relevant words, phrases, sentences, or sections. 2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant. 2.3. You might decide that something is relevant to code because: *it is repeated in several places; *the interviewee explicitly states that it is important; *you have read about something similar in reports, e.g. scientific articles; *it reminds you of a theory or a concept; *or for some other reason that you think is relevant. You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you. It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds. STEP 3, decide which codes are the most important, and create categories by bringing several codes together 3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand. 3.2. You can create new codes by combining two or more codes. 3.3. You do not have to use all the codes that you created in the previous step. 3.4. In fact, many of these initial codes can now be dropped. 3.5. Keep the codes that you think are important and group them together in the way you want. 3.6. Create categories. (You can call them themes if you want.) 3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever. 3.8. Be unbiased, creative and open-minded. 3.9. Your work now, compared to the previous steps, is on a more general, abstract level. You are conceptualizing your data. STEP 4, label categories and decide which are the most relevant and how they are connected to each other 4.1. Label the categories. Here are some examples: Adaptation (Category) Updating rulebook (sub-category) Changing schedule (sub-category) New routines (sub-category) Seeking information (Category) Talking to colleagues (sub-category) Reading journals (sub-category) Attending meetings (sub-category) Problem solving (Category) Locate and fix problems fast (sub-category) Quick alarm systems (sub-category) 4.2. Describe the connections between them. 4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study. STEP 5, some options 5.1. Decide if there is a hierarchy among the categories. 5.2. Decide if one category is more important than the other. 5.3. Draw a figure to summarize your results. STEP 6, write up your results 6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results. 6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example: *results from similar, previous studies published in relevant scientific journals; *theories or concepts from your field; *other relevant aspects. STEP 7 Ending remark Nb: it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.) Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze: *notes from participatory observations; *documents; *web pages; *or other types of qualitative data. STEP 8 Suggested reading Alan Bryman's book: 'Social Research Methods' published by Oxford University Press. Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE. Text and video (including audio) © Kent Löfgren, Sweden
Views: 785089 Kent Löfgren
Top 5 BI Tools | Business Intelligence Tools | BI Tools | Intellipaat
 
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Intellipaat BI Architect Masters Training: https://goo.gl/zFPqhx This Intellipaat top 5 BI Tools is a snippet of information about the top 5 Business Intelligence Tools that's been in demand across the globe. Do check below links to learn all the top BI Tools and do subscribe to Intellipaat channel to get regular updates on them: https://goo.gl/hhsGWb Tableau training: https://goo.gl/6WNCg3 Informatica training: https://goo.gl/JuLhRK MSBI training: https://goo.gl/Yno5tA Power BI training: https://goo.gl/uLjnNx IBM Cognos training: https://goo.gl/TBbdSR Are you interested to learn any of the top 5 BI tools mentioned in the video to get high paying jobs? Enroll in our Intellipaat courses & become a certified Professional (https://goo.gl/zFPqhx). All Intellipaat trainings are provided by Industry experts and is completely aligned with industry standards and certification bodies. If you’ve enjoyed this top 5 BI tools video, Like us and Subscribe to our channel for more informative tutorials. Got any questions about the top 5 BI tools? Ask us in the comment section below. ---------------------------- Intellipaat Edge 1. 24*7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs 5. Industry Oriented Course ware 6. Life time free Course Upgrade #top5bitools #businessintelligencetools #bitools ------------------------------ For more Information: Please write us to [email protected], or call us at: +91- 7847955955 Website: https://goo.gl/zFPqhx Facebook: https://www.facebook.com/intellipaatonline LinkedIn: https://www.linkedin.com/in/intellipaat/ Twitter: https://twitter.com/Intellipaat
Views: 18273 Intellipaat
Exponential Smoothing in Excel using Data analysis tools (Machine Learning/Statistics)
 
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After Moving Average (https://youtu.be/nPyPLRUkfRY), let's have a look at Exponential Smoothing in excel. This technique is used for smoothing time series data using the exponential window function. In Moving Average the past values are weighted equally, on the other hand exponential functions are used to assign exponentially decreasing weights over time
Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
 
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Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 327705 CS Dojo
Module 1: Data Analysis in Excel
 
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This video is part of the Analyzing and Visualizing Data with Excel course available on EdX. To sign up for the course, visit: http://aka.ms/edxexcelbi
Views: 438824 DAT206x
Why Use R? - R Tidyverse Reporting and Analytics for Excel Users
 
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https://www.datastrategywithjonathan.com Free YouTube Playlist https://www.youtube.com/playlist?list=PL8ncIDIP_e6vQ0uQofezvKv3yPnL5Unxe From Excel To Big Data and Interactive Dashboard Visualizations in 5 Hours If you use Excel for any type of reporting or analytics then this course is for you. There are a lot of great courses teaching R for statistical analysis and data science that can sometimes make R seem a bit too advanced for every day use. Also since there are many different ways of using R that can often add to the confusion. The reality is that R can be used to make your every day reporting analytics that you do in Excel much faster and easier without requiring any complex statistical techniques while at the same time giving you a solid foundation to expand into those areas if you so wish. This course uses the Tidyverse standards for using R which provides a single, comprehensive and easy to understand method for using R without complicating things via multiple methods. It's designed to build upon the the skills you are already familiar with in Excel to shortcut your learning journey. If you're looking to learn Advanced Excel, Excel VBA or Databases then you need to check out this video series. In this videos series, I will show you how to use Microsoft Excel in different ways that will make you far more effective at working with data. I'm also going to expand your knowledge beyond Excel and show you tips, tricks, and tools from other top data analytics tools such as R Tidyverse, Python, Data Visualisation tools such as Tableau, Qlik View, Qlik Sense, Plotly, AWS Quick Sight and others. We'll start to touch on areas such as big data, machine learning, and cloud computing and see how you can develop your data skills to get involved in these exciting areas. Excel Formulas such as vlookup and sumifs are some of the top reasons for slow spreadsheets. Alternatives for vlookup include power query (Excel 2010 and Excel 2013) which has recently been renamed to Get and Transform in Excel 2016. Large and complex vlookup formulas can be also done very efficiently in R. Using the R Tidyverse libraries you can use the join functions to merge millions of records effortlessly. In comparison to Excel Vlookup, R Tidyverse Join can pull on multiple columns all at the same time. Microsoft Excel Power Query and R Tidyverse Joins are similar to the joins that you do in databases / SQL. The benefit that they have over relational databases such as Microsoft Access, Microsoft SQL Server, MySQL, etc is that they work in memory so they are actually much faster than a database. Also since they are part of an analytics tool instead of a database it is much faster and easier to build your analysis and queries all in the same tools. My very first R Tidyverse program was written to replace a Microsoft Access VBA solution which was becoming complicated and slow. Note that Microsoft Access is very limited in analytics functions and is missing things as simple as Median. Even though I had to learn R programming from scratch and completely re-write the Microsoft Access VBA solution it was so much easier and faster. It blew my mind how much easier R programming with R Tidyverse was than Microsoft Access VBA or Microsoft Excel VBA. If you have any VBA skills or are looking to learn VBA you should definitely checkout my videos on R Tidyverse. To understand why R Tidyverse is so much easier to work with than VBA. R Tidyverse is designed to work directly with your data. So If you want to add a calculated column that’s around one line of script. In Excel VBA, the VBA is used to control the DOM (Document Object Model). In Excel that means that you VBA controls things like cells and sheets. This means your VBA is designed to capture the steps that you would normally do manually in Microsoft Excel or Microsoft Access. VBA is not actually designed to work directly with your data. Note the most efficient path is to reduce the data pulled down from the database in the first place. This is referring to the amount of data you are pulling down from your data warehouse or data lake. It makes no sense to pull data from a data warehouse / data lake to pull into another database to query add joins / lookups to then pull it into Excel or other analysis tool. Often analyst build these intermediate databases because they either don’t have control of the data warehouse or they need to join additional information. All of these operations are done significantly faster in a tool such as R Tidyverse or Microsoft Excel Power Query.
Views: 17981 Jonathan Ng
Introduction to Data Science with R - Data Analysis Part 1
 
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Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 1047488 David Langer
How to become a Data Analyst in India - Course and career
 
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This video discuss How to become a data analyst in India. For more videos on Jobs &Careers :https://www.youtube.com/channel/UCEFTTJFLp4GipA7BLZNTXvA?view_as=subscriber For aptitude classes :https://www.youtube.com/watch?v=lxm6ez2cx6Y&list=PLjLhUHPsqNYnM1DmZhIbtd9wNhPO1HGPT Every business collects data such as sales figures, market research, logistics, or transportation costs. A data analyst's job is to take that data and analyse it to help companies make better business decisions. Some examples of a data analyst basic job functions include: 1) estimating market shares; 2) establishing a price of new materials for the market; 3) reducing transportation costs; 4) timing of sales and 5) figuring out when to hire or reduce the workforce.Data analysts are responsible for collecting, manipulating, and analyzing data. How To Get There? By obtaining a university degree, learning important analytical skills, and gaining valuable work experience, you can become a successful data analyst. A bachelor's degree is needed for most entry-level jobs, and a master's degree will be needed for many upper-level jobs. To become an initial level data analyst, you’ll have to earn a degree in a subject such as mathematics, statistics, economics, marketing, finance, or computer science. Higher level data analyst jobs may require a master’s or doctoral degree, and they usually guarantee higher pay. Individuals looking for data analyst jobs must be knowledgeable in computer programs such as Microsoft Excel, Microsoft Access, SharePoint, and SQL databases. Data analysts also must have good communication skills, as they must have an open line of communication with the companies with which they work. Lets see some of the Best courses on Analytics offered in India. 1. Advanced Analytics for Management – IIM This program enables practitioners, managers, and decision-makers to use advanced analytics for better decision-making 2. Analytics Essentials – IIIT, Bangalore “Analytics Essentials”is a 3 months week-end program by International Institute of Information Technology Bangalore (IIITB)providing a foundational certification course in Business Analytics 3. Business Analytics and Intelligence (BAI) – IIM Bangalore This course provides in-depth knowledge of handling data and Business Analytics’ tools that can be used for fact-based decision-making. The participants will be able to analyse and solve problems from different industries such as manufacturing, service, retail, software, banking and finance, sports, pharmaceutical, aerospace etc. 4. Certificate Program in Business Analytics – ISB, Hyderabad A combination of classroom and Technology aided learning platform, .Participants will typically be on campus for a 5 day schedule of classroom learning every alternate month for a span of 12 months, which would ideally be planned to include a weekend. 5. Data Analysis Online courses – SRM University SRM University offers part time online courses in data analysis in collaboration with Coursera, edX, Udacity. 6. Executive Program in Business Analytics – IIM Calcutta This executive 1 year long distance program is designed to expose participants to the tools and techniques of analytics. The program covers topics such as Data Mining, Soft Computing, Design of Experiments, Survey Sampling, Statistical Inference, Investment Management, Financial Modelling, Advanced marketing Research etc. 7. Executive Program in Business Analytics and Business Intelligence – IIM Ranchi Course duration is 3 months. Classes will be conducted by eminent professors and industry experts in the weekends in Mumbai/ Kolkata /Delhi /Bengaluru and in addition to these, there will be one-week learning in IIM Ranchi. 8. Jigsaw Academy courses Jigsaw Academy provides some online analytics courses.Their courses include; Foundation Course in Analytics Data Science Certification Human Resources (HR) Analytics Course Big Data Analytics Using Hadoop and R Advanced Certification in Retail Analytics Advanced Course in Financial Analytics Analytics with R Great Lakes PG Course in Business Analytics 9. M. Tech. Computer Science and Engineering with Specialization in Big Data Analytics – VIT VIT offers full time course in Big Data analysis to promote an academic career for further research in theoretical as well as applied aspects of Big Data Analytics 10. M.Tech (Database Systems) – SRM University SRM University offers a two year full time course in database systems where the students are exposed to theoretical concepts complemented by related practical experiments. 11. M.Tech Computer Engineering and Predictive Analytics – Crescent Engineering College Salary The Salary of Data analysts depends on job responsibilities. An entry-level data analyst with basic technical tools might be looking at anything from Rs. 5 lakhs to 12 lakhs per year. A senior data analyst with the skills of a data scientist can command a high price. #dataanalyst #careeroptions #datascience
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1603077 ExcelIsFun
Descriptive Statistics - Excel Data Analysis ToolPak
 
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Descriptive Statistics Generation - Excel Data Analysis ToolPak. Data set used can be downloaded at http://www.learnanalytics.in/blog/wp-content/uploads/2013/04/car_sales.xlsx
Views: 33777 Learn Analytics
Data Analytics Tools and Curriculum at Toronto School of Management
 
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Several commonly used Data Analytics tools are incorporated in Toronto School of Management’s curriculum for Diploma in Data Analytics Co-op (https://bit.ly/2Tof2U6 ). They include the 2 top tools: Tableau and SAS programming. In this video, Dr. Said Azzam discusses the importance of data visualization, the demand of SAS programming and different data categories learned in the course. Dr. Said Azzam advises that communication is key within this team-work environment. He supports TSoM students fully and is always open to questions. Visit Toronto School of Management: https://www.torontosom.ca Video courtesy of https://www.tableau.com/ and https://www.sas.com/en_ca/learn/academic-programs.html
Quick Data Analysis with Google Sheets | Part 1
 
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Spreadsheet software like Excel or Google Sheets are still a very widely used toolset for analyzing data. Sheets has some built-in Quick analysis features that can help you to get a overview on your data and very fast get to insights. #DataAnalysis #GoogleSheet #measure 🔗 Links mentioned in the video: Supermetrics: http://supermetrics.com/?aff=1014 GA Demo account: https://support.google.com/analytics/answer/6367342?hl=en 🎓 Learn more from Measureschool: http://measureschool.com/products GTM Copy Paste https://chrome.google.com/webstore/detail/gtm-copy-paste/mhhidgiahbopjapanmbflpkcecpciffa 🚀Looking to kick-start your data journey? Hire us: https://measureschool.com/services/ 📚 Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books 📷 Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear Our tracking stack: Google Analytics: https://analytics.google.com/analytics/web/ Google Tag Manager: https://tagmanager.google.com/ Supermetrics: http://supermetrics.com/?aff=1014 ActiveCampaign: https://www.activecampaign.com/?_r=K93ZWF56 👍 FOLLOW US Facebook: http://www.facebook.com/measureschool Twitter: http://www.twitter.com/measureschool
Views: 20725 Measureschool
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 192369 APMonitor.com
Introduction to Multivariate Data Analysis
 
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Brad Swarbrick, Vice President of Business Development at CAMO Software, gives a shor tintroduction to multivariate data analysis, discusses some of its applications and how these powerful analytical tools are being used to improve products and manufacturing processes in a wide range of industries. Brad Swarbrick is a pharmaceutical industry specialist for CAMO Software with over 20 years experience in the application of chemometrics techniques to spectroscopic analysers and process control systems. He was part of the Pfizer Global Process Analytical Technology (PAT) group in Australia and developed the NIR spectroscopy and PAT programs for Sigma Pharmaceuticals, Australia's largest pharmaceuticals manufacturer. For the past 3 years Brad has been based in Europe, during which time he has helped a number of leading manufacturers realize major process and quality improvements in the pharmaceutical, agricultural, chemical and downstream oil & gas industries across Europe, North America and Asia. Brad has a B.Sc (Hons) in Science and Mathematics, majoring in Chemometrics. He is the Chair of the Community of Practice in PAT, regional board director of the Australian ISPE (International Society for Pharmaceutical Engineering) affiliate, and was a member of the ASTM E55 sub-committee on PAT. Brad has been an invited expert speaker in a wide range of global conferences on PAT, NIR and Quality by Design (QbD), and has authored a number of whitepapers and peer-reviewed journal articles as well as the popular reference book Multivariate Data Analysis for Dummies. In addition to his work at CAMO, Brad has recently taken the role of pharmaceutical editor for the prestigious Journal of NIR Spectroscopy.
Views: 37500 Camo Analytics
What Techniques Do Business Analysts Use?
 
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This KnowledgeKnugget™ (KK) is part of an eCourse "Business Analysis Defined". VIEW COURSE OUTLINE at http://businessanalysisexperts.com/product/video-course-business-analysis-defined/. Also available as Paperback or Kindle eBook at http://www.amazon.com/dp/B00K7MM50O/. DESCRIPTION: Although the field of IT Business Analysis offers great career opportunities for those seeking employment, some business analysis skills are essential for any adult in the business world today. For example, the task of defining the requirements for an IT solution is handed to Business Analysts as well as Subject Matter Experts, Developers, System Analysts, Product Owners, Project Managers, Line Managers, or any other business expert. Applying business analysis techniques to define their business needs results in much higher chances for a successful IT project. In this KnowledgeKnugget™ you will learn what business analysis techniques and tools are most commonly used around the world based on surveys of actual business analysts. This KnowledgeKnugget™ answers questions like: 1. What are the primary activities in business analysis? 2. What tools or techniques do they use? To view more IT requirements training, visit the Business Analysis Learning Store at http://businessanalysisexperts.com/business-analysis-training-store/. PARTIAL TRANSCRIPT: Business analysis is the process of studying a business or any other organization to identify business opportunities / problem areas and suggest potential solutions. A wide range of people with various titles, roles and responsibilities actually apply business analysis techniques within an organization. There are three fundamentally different flavors or levels of business analysis: 1. Strategic Business Analysis (aka Enterprise Analysis) (http://businessanalysisexperts.com/strategic-business-analysis/ ) 2. Tactical Business Analysis (http://businessanalysisexperts.com/tactical-business-analysis/) 3. Operational Business Analysis (http://businessanalysisexperts.com/operational-business-analysis/Operational Business Analysis) Strategic Business Analysis is the study of business visions, goals, objectives, and strategies of an organization or an organizational unit to identify the desired future. It encompasses the analysis of existing organizational structure, policies, politics, problems, opportunities, and application architecture to build a business case for change. This analysis employs business analysis techniques such as Variance Analysis, Feasibility Analysis, Force Field Analysis, Decision Analysis, and Key Performance Indicators to support senior management in the decision-making process. The primary outcome of this work is a set of defined, prioritized projects and initiatives that the organization will undertake to create the desired future. If the initiative includes the development of software using an Agile Software Development Methodology (SDM) (http://businessanalysisexperts.com/product/business-analysis-agile-methodologies/), strategic business analysis techniques identify themes and/or epics, and initiate a product backlog. Tactical Business Analysis is at the project or initiative level to flush out the details of the proposed solution and to ensure that it meets the needs of the business community. Commonly used business analysis techniques at this level include Stakeholder Identification (http://businessanalysisexperts.com/product/how-to-identify-stakeholders-it-projects/), Interviewing (http://businessanalysisexperts.com/product/requirements-elicitation-gathering-business-stakeholder-it-requirements/), Facilitation (http://businessanalysisexperts.com/product/how-to-facilitate-requirements-gathering-workshops/), Baselining, Coverage Matrices, MoSCoW Analysis (http://businessanalysisexperts.com/product/requirements-prioritization-two-simple-techniques/), Benchmarking, Business Rules Analysis, Change Management, Process and Data Modeling (http://businessanalysisexperts.com/product/business-data-modeling-informational-requirements/), and Functional Decomposition (http://businessanalysisexperts.com/product/video-course-exposing-functional-and-non-functional-requirements/). In an Agile environment, Tactical Business Analysis adds to the Product Backlog and/or Release Plans expressed in Themes, Business Epics, Architecture Epics, User Stories (http://businessanalysisexperts.com/product/video-course-writing-user-stories/), and User Story Epics. In a traditional setting, the primary outcome of Tactical Business Analysis is a set of textual and/or modeled Business and Stakeholder Requirements (http://businessanalysisexperts.com/product/video-course-writing-requirements/). ..........
Views: 310370 BA-EXPERTS
Digital Analytics Introduction | Digital Marketing Tutorial For Beginners | Simplilearn
 
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This video will help participants develop a comprehensive knowledge of the various frameworks, tools and techniques pertaining to digital analytics. Participants will learn to track campaign performance, access visitor behavior, and gain the competitive intelligence required to drive continual optimization in their marketing campaigns and improve the online customer experience. #DigitalMarketing #SimplilearnDigitalMarketing #DigitalMarketingCourse #DigitalMarketingCertification #DigitalMarketingCertifiedAssociate #DigitalAnalytics Subscribe to Simplilearn channel for more Social Media Marketing Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 For More Digital Marketing Tutorial videos, check our Digital Marketing tutorial for beginners playlist: https://www.youtube.com/watch?v=xA_yMYN19ug&list=PLEiEAq2VkUULa5aOQmO_al2VVmhC-eqeI Digital Marketing Articles: https://www.simplilearn.com/resources/digital-marketing?utm_campaign=Analytics-Intro-upgbtXil10E&utm_medium=Tutorials&utm_source=youtube To Gain in-depth knowledge of Digital Analytics and other Digital Marketing concepts, check out Advanced Web Analytics Course: https://www.simplilearn.com/digital-marketing/digital-marketing-certified-associate-training?utm_campaign=Analytics-Intro-upgbtXil10E&utm_medium=Tutorials&utm_source=youtube ------------------------------------- What’s the focus of this Advanced Web Analytics course? Advanced Web Analytics is the science of analysis that focuses on Internet data. It involves the collection, analysis, and data-informed decisions leading to the optimization of an organization's digital ecosystem and supporting business processes. Data from websites, mobile applications, social media, Internet of Things, or third party sources are commonly combined with back-office Customer Relationship Management (CRM) and Sales systems to inform business decisions. Web Analytics has become an integral part of core business strategies, workflow optimization, and maintaining a competitive edge. This Web Analytics course covers fundamental concepts of analytics and deep dives into web, social, content and mobile analytics common scenarios and covers the popular web analytics tools used by marketers across the major industry domains. Although this course approaches on learning Digital Analytics from a managerial perspective, it will showcase tips and techniques for the most common google web analytics platform and several other relevant tools along the way. -------------------------------------- What are the course objectives of this Advanced Web Analytics Course? Advanced Web Analytics training gives participants well-rounded knowledge in digital data analytics, including: 1. How to leverage data from various sources to conduct quantitative and qualitative research, and deliver actionable, data-informed business insights 2. How digital data analytics drives important insights for all aspects of your customer’s life cycle across the entire digital world 3. Uncover and learn about the various analysis capabilities enabled through digital data 4. How to better inform business decisions with rigorous analysis techniques ---------------------------------------- Who should take this course? This Digital Analytics training module is suitable for professionals who want to learn and specialize in digital analytics to boost their skillsets in the digital marketing industry and beyond. This course is best suited for participants who are: 1. Online Web Analytics Implementers 2. Online Web Analytics Data Reporters 3. Digital Analysts 4. Digital Marketers 5. Managers 6. Web Analytics Certification Aspirants 7. Digital Analytics Certification Aspirants ---------------------------------------- For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 5219 Simplilearn
Top 5 Algorithms used in Data Science | Data Science Tutorial | Data Mining Tutorial | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This tutorial will give you an overview of the most common algorithms that are used in Data Science. Here, you will learn what activities Data Scientists do and you will learn how they use algorithms like Decision Tree, Random Forest, Association Rule Mining, Linear Regression and K-Means Clustering. To learn more about Data Science click here: http://goo.gl/9HsPlv The topics related to 'R', Machine learning and Hadoop and various other algorithms have been extensively covered in our course “Data Science”. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 108755 edureka!
Introduction To Business Analytics With R | Data Science With R Training
 
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This is an introduction video to the course business analytics foundation with R tools in which you will be able to learn the difference between analysis and analytics, Understand what is analytics and know the different stages in analytics, Understand where analytics is applied and the process involved in it, get an overview of the various topics covered in different lessons, know the career path of a business analyst, know the popular tools used in analyitcs, understand the role of a data scientist, know the processes involved in analytics, defining a problem statement, collecting and summarizing the data, Detecting and treating outliers in the data. Data Scientist with R Language Certification Training: http://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=Introduction-to-Business-Analytics-Foundation-20Neb7zkHVQ&utm_medium=SC&utm_source=youtube For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 34013 Simplilearn
What Is SAS | SAS Tutorial For Beginners | SAS Programming | SAS Training | Edureka
 
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This Edureka "What Is SAS" video will help you get started with SAS. This video will also introduce you to Data Analytics and SAS Programming concepts. Check out our SAS Tutorial Playlist: https://goo.gl/aywPvo This video helps you to learn following topics: 1. Data Analytics 2. Data Analytical Tools 3. Why SAS? 4. What Is SAS? 5. SAS Framework 6. SAS Programming Concepts 7. SAS Applications Subscribe to our channel to get video updates. Hit the subscribe button above. #SAS #WhatIsSAS #SASProgramming #SASTraining #SASforbeginners #SASTutorial #SASBuildingBlocks #SASDataAndProcSteps ----------------------------------------------------------------- How it Works? 1. This is a 4 Week Instructor led Online Course, 25 hours of assignment and 20 hours of project work. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! -------------------------------------------------------------------- About The Course Edureka's SAS Course is designed to provide knowledge and skills to become a successful Analytics professional. It starts with the fundamental concepts of rules of SAS as a Language to an introduction to advanced SAS topics like SAS Macros. ---------------------------------------------------------------------- Who should go for this course? This course is designed for professionals who want to learn widely acceptable data mining and exploration tools and techniques, and wish to build a booming career around analytics. The course is ideal for: 1. Analytics professionals who are keen to migrate to advanced analytics 2. BI /ETL/DW professionals who want to start exploring data to eventually become data scientist 3. Project Managers to help build hands-on SAS knowledge, and to become a SME via analytics 4. Testing professionals to move towards creative aspects of data analytics 5. Mainframe professionals 6. Software developers and architects 7. Graduates aiming to build a career in Big Data as a foundational step ----------------------------------------------------------------------- Why learn SAS? The Edureka SAS training certifies you as an ‘in demand’ SAS professional, to help you grab top paying analytics job titles with hands-on skills and expertise around data mining and management concepts. SAS is the primary analytics tool used by some of the largest KPOs, Banks like American Express, Barclays etc., financial services irms like GE Money, KPOs like Genpact, TCS etc., telecom companies like Verizon (USA), consulting companies like Accenture, KPMG etc use the tool effectively. For more information, please write back to us at [email protected] Call us at US: 1844 230 6362(toll free) or India: +91-90660 20867 Website: https://www.edureka.co/sas-training Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 188793 edureka!
Minitab Tutorial | Minitab Training Video | What is Minitab? | Introduction to Minitab
 
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This video compounded by 4 lessons as mentioned below. • Lesson 01 – Introduction to Minitab • Lesson 02 – Minitab Interoperability • Lesson 03 – Lean Six Sigma Green Belt Case Study • Lesson 04 – Case Study on Lean Six Sigma Green Belt Minitab Certification Training: https://www.simplilearn.com/quality-management/minitab-training?utm_campaign=Minitab-tutorial-KJjfccxVcss&utm_medium=SC&utm_source=youtube #minitab #minitabtutorialforbeginners #minitabtutorial #minitab17tutorial #minitab17 So here are the objectives and summaries for the above chapters, that you will be able learn after completing this training edition. Lesson 01 – Objectives • Comprehend the overview and importance of Minitab • Review the Worksheet Format and Structure • Define Data Window Column Conventions • Define Other data Window Conventions • Discuss the Menu Bar options This course ensures that you learn the practical applications of the latest version of the statistical tool, Minitab® 17 and excel at the tools used by both Lean Six Sigma Green Belt and Black Belt professionals. The course covers 9 case studies in the domains of Healthcare, IT and IT Services, and Manufacturing, and each case study describes a problem and its solution using Minitab® 17. What are the course objectives? By the end of Minitab training you will be able to: 1. Process key statistical data operations using Minitab 2. Export data to various MS office applications 3. Understand and apply various statistical tools in various quality projects 4. Understand and remove common pitfalls in data analysis 5. Master all statistical tools/topics needed for Green/Black belt projects Who should take this course? Minitab is most beneficial for organizations that encourage employees to take up efficiency/ quality projects and bring in key insights using data analysis. This course is most suited for: 1. Individuals looking forward to learn data analysis using Minitab 2. Analysts 3. Quality System Managers 4. Quality Engineers 5. Quality Supervisors 6. Quality Auditors For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 138698 Simplilearn
Data Analysis and Statistics for Decision Making Using StatTools
 
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John McKenzie demonstrates how StatTools can be easily used for managing your data set, deriving descriptive statistics, exploratory data analysis, determining normality, inferential statistics (both parametric and non-parametric), time series, regression, logistic regression and quality control. Originally Recorded: August 2008
Views: 7724 Palisade