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 Duration 14 hours

Course Outline

Lesson 1 - Fundamentals of SQL: 

  • Select statements
  • Types of Joins
  • Indexes
  • Views
  • Subqueries
  • Union
  • Table creation
  • Data loading
  • Data dumping
  • NoSQL

Lesson 2 - Data Modeling:

  • Transaction-based ER systems
  • Data warehousing 
  • Data warehouse models
    • Star schema
    • Snowflake schemas
  • Slowly changing dimensions (SCD)
  • Structured and unstructured data
  • Various table storage engines:
    • Column-based
    • Document-based
    • In-Memory

Lesson 3 - Indexing in the NoSQL and Data Science Context

  • Constraints (Primary)
  • Index-based scanning
  • Performance tuning

Lesson 4 - NoSQL and Unstructured Data

  • Scenarios for using NoSQL
  • Eventually consistent data
  • Schema on read vs. Schema on write

Lesson 5 - SQL for Data Analytics

  • Windowing functions
  • Lateral Joins
  • Lead & Lag

Lesson 6 - HiveQL

  • SQL support
  • External and internal tables
  • Joins
  • Partitions
  • Correlated subqueries
  • Nested queries
  • Appropriate use cases for Hive

Lesson 7 - Redshift

  • Design and structure
  • Locks and shared resources
  • Differences from Postgres
  • Appropriate use cases for Redshift

Requirements

  • A foundational understanding of databases
  • Practical experience with SQL is advantageous.

Target Audience

  • Business analysts
  • Software developers
  • Database developers

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