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Course Outline

Lesson 1 - SQL Fundamentals

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

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
  • Different table type storage engines:
    • Column-based
    • Document-based
    • In-memory

Lesson 3 - Indexing in the NoSQL/Data Science Landscape

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

Lesson 4 - NoSQL and Unstructured Data

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

Lesson 5 - SQL for Data Analytics

  • Window functions
  • Lateral Joins
  • Lead & Lag functions

Lesson 6 - HiveQL

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

Lesson 7 - Redshift

  • Design and structure
  • Locks and shared resources
  • Differences from Postgres
  • When to use Redshift

Requirements

  • A foundational understanding of databases.
  • Experience with SQL is advantageous.

Audience

  • Business analysts
  • Software developers
  • Database developers
 14 Hours

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