Course Code: sqldatasci
Duration: 14 hours
Prerequisites:
  • An understanding of  databases
  • Experience with SQL an asset.

Audience

  • Business analysts
  • Software developers
  • Database developers
Overview:

This instructor-led, live training (online or onsite) is aimed at software developers, managers, and business analyst who wish to use big data systems to store and retrieve large amounts of data.

By the end of this training, participants will be able to:

  • Query large amounts of data efficiently.
  • Understand how Big Data system store and retrieve data
  • Use the latest big data systems available
  • Wrangle data from data systems into reporting systems
  • Learn to write SQL queries in:
    • MySQL
    • Postgres
    • Hive Query Language (HiveQL/HQL)
    • Redshift 

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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
Sites Published:

United Arab Emirates - SQL For Data Science and Data Analysis

Qatar - SQL For Data Science and Data Analysis

South Africa - SQL For Data Science and Data Analysis

Canada - SQL For Data Science and Data Analysis

USA - SQL For Data Science and Data Analysis

Ireland - SQL For Data Science and Data Analysis

España - SQL For Data Science and Data Analysis

Nederland - SQL For Data Science and Data Analysis

Singapore - SQL For Data Science and Data Analysis

Colombia - SQL For Data Science and Data Analysis

Venezuela - SQL For Data Science and Data Analysis

United Kingdom - SQL For Data Science and Data Analysis

Bolivia - SQL For Data Science and Data Analysis

Indonesia - SQL For Data Science and Data Analysis

Kazakhstan - SQL For Data Science and Data Analysis

Moldova - SQL For Data Science and Data Analysis

Morocco - SQL For Data Science and Data Analysis

Tunisia - SQL For Data Science and Data Analysis

Kuwait - SQL For Data Science and Data Analysis

Oman - SQL For Data Science and Data Analysis

Slovakia - SQL For Data Science and Data Analysis

Kenya - SQL For Data Science and Data Analysis

Nigeria - SQL For Data Science and Data Analysis

Botswana - SQL For Data Science and Data Analysis

Slovenia - SQL For Data Science and Data Analysis

Croatia - SQL For Data Science and Data Analysis

Serbia - SQL For Data Science and Data Analysis

Bhutan - SQL For Data Science and Data Analysis

Nepal - SQL For Data Science and Data Analysis

Uzbekistan - SQL For Data Science and Data Analysis