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What you'll get

  • Job Credibility
  • Certification Valid for Life
  • On-demand video*
  • E-Book
  • Self-Paced Learning
  • Certificate of Completion

Exam details

  • Mode of Exam : Online
  • Duration : 1 Hour
  • Multiple Choice Questions are asked
  • No. of Questions are asked : 50
  • Passing Marks : 25 (50%)
  • There is no negative marking

In this course, we are going to learn how Data Analytics can be used with SQL and along with that you will also learn some basics of SQL which will help you understand the concepts more in depth.

You will be allowed a full access to the course, after you buy successfully and will also be able to attempt exam before even finishing any course module.

It is an online SQL Data Analytics Course, which means you are free to take exam anytime anywhere.

But note, before taking exam, you should have knowledge about the course, until then you will be able to attempt exam and can pass it with at least 50%

There are more benefits after completion of the course and certificate, Students who already owned the certificate for the same, have successfully placed in well-operated organization.

Course Content

Total: 43 lectures
  • What is Data Analysis?
  • Why SQL?
  • Database Types
  • Conclusion
  • Types of Data
  • SQl Query Structure
  • Profiling: Distributions
  • Profiling: Data Quality
  • Preparing : Data Cleaning
  • Preparing: Shaping Data
  • Conclusion
  • Data, Datetime, and Time Maniplations
  • The Retail Sales Data Set
  • Trending the Data
  • Rolling Time Windows
  • Analyzing with Seasonality
  • Conclusion
  • Cohort A Useful Analysis Framework
  • The legislators Data Set
  • Rentention
  • Related Cohort Analyses
  • Cross-Section Analysis
  • Why Text Analysis with SQL?
  • The UFO Sightings Data Set
  • Text Characteristics
  • Text Parsing
  • Text Transformations
  • Finding Elements Within Larger Blocks of Text
  • Constructing and Reshaping Text
  • Capabilities and Limits of SQL for Anomaly Detection
  • The Data Set
  • Detecting Outliers
  • Forms of Anomalies
  • Handling Anomalies
  • Strengths and Limits of Experiment Analysis with SQL
  • The Data Set
  • Types of Experiments
  • Challenges with Experiments and Options for Rescuing Flawed Experiments
  • When Controlled Experiments Aren’t Possible: Alternative Analyses
  • When to Use SQL for Complex Data Sets
  • Code Organization
  • Organizing Computations
  • Managing Data Set Size and Privacy Concerns


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