Course Outline

Lesson 1 - SQL basics: 

  • Select statements
  • Join types
  • Indexes
  • Views
  • Subqueries
  • Union
  • Creating tables
  • Loading data
  • Dumping data
  • NoSQL

Lesson 2 - Data Modeling:

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

Lesson 3 - Index in the NoSQL/Data science world

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

Lesson 4 - NoSQL and non-structured data

  • When to use NoSQL
  • Eventually consistent data
  • Schema on read vs. Schema on write

Lesson 5 - SQL for data analytics

  • Windowing function
  • Lateral Joins
  • Lead & Lag

Lesson 6 - HiveQL

  • SQL Support
  • External and Internal Tables
  • Joins
  • Partitions
  • Correlated subqueries
  • Nested queries
  • When to use Hive

Lesson 7 - Redshift

  • Design and structured
  • Locks and shared resources
  • Postgres differences
  • When to use redshift

 

Requirements

  • An understanding of  databases
  • Experience with SQL an asset.

Audience

  • Business analysts
  • Software developers
  • Database developers
 14 Hours

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