Data Analytics: Principles, Tools, and Practices

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About This Course

Skills You’ll Get

1

Preface

2

Database Management System

  • Database and database management system
  • DB objects
  • Conclusion
  • Questions
3

Online Transaction Processing and Data Warehouse

  • Introduction
  • Online transaction processing
  • Need of data warehouse
  • Dimensional modeling used in DW design
  • Types of schemas
  • ETL and other tools sets available in market
  • Conclusion
  • Questions
4

Business Intelligence and Its Deeper Dynamics

  • Business intelligence
  • Data quality: a real challenge
  • Structured Versus Unstructured
  • Data Lake
  • Modern business intelligence system
  • Conclusion
  • Questions
5

Introducing Data Visualization

  • Presenting data visualization
  • Ring chart
  • Stacked area chart
  • Visualization dashboards
  • Introduction to reporting tools
  • Tableau
  • High charts
  • Conclusion
  • Questions
6

Advanced Data Visualization

  • Types of advanced data visualization
  • Data visualization trends
  • Introducing data visualization tools
  • Conclusion
  • Questions
7

Introduction to Big Data and Hadoop--Too Huge to Avoid

  • Introduction and need of big data
  • Introducing Hadoop and HDFS system
  • The Hadoop distributed file system
  • Conclusion
  • Points to remember
8

NoSQL and MapReduce--Too Huge to Avoid

  • What is NoSQL?
  • Uses of NoSQL
  • Types of NoSQL database
  • Programming MapReduce jobs
  • What is MapReduce?
  • How MapReduce works?
  • Conclusion
  • Points to remember
9

Application of Big Data—Real Use Cases

  • Big data applications in healthcare
  • What is big data in healthcare?
  • Why do we need big data analytics in healthcare?
  • Twelve big data applications in healthcare
  • List of 12 big data examples in healthcare
  • Applications of big data in finance
  • Big data applications in retail
  • Big data benefits for retail
  • Big data application in travel
  • Big data applications in media
  • Conclusion
  • Questions
10

Introducing Machine Learning - Making Machine to Run the Show

  • Introduction
  • Need for machine learning
  • Supervised learning
  • Conclusion
11

Advanced Concepts to Machine Learning: Making Machine to Run the Show

  • Predictive learning--predictive analytic and machine learning
  • Predictive analytics models
  • Deep learning
  • Deep learning architecture
  • Deep Learning Algorithms
  • YOLO--You Just Look Once
  • Natural Language Programming
  • Conclusion
  • Points to remember
12

Application of Machine Learning

  • Machine learning applications in healthcare
  • Machine learning applications in finance
  • Machine learning applications in retail
  • Key benefits of machine learning in retail
  • Wrapping up
  • Advantages of predictive analytics for machine learning in retail
  • Applications in Brick-and-Mortar retail
  • Machine learning applications in travel
  • ML, AI, and big data analytics in the travel and hospitality industry
  • Machine learning applications in media
  • The future of machine learning
  • Conclusion
  • Points to remember

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