Data Warehouse is a collection of software tool that help analyze large volumes of disparate data. The goal is to derive profitable insights from the data. This eBook covers advance topics like Data Marts, Data Lakes, Schemas amongst others.
Section 1- Introduction
- What Is Data Warehousing? Types, Definition & Example (First Chapter FREE)
- Database vs Data Warehouse: Key Differences
- Data Warehouse Architecture, Concepts and Components
- ETL (Extract, Transform, and Load) Process
- ETL vs ELT: Must Know Differences
Section 2- Advanced Stuff
- What is Data Modelling? Conceptual, Logical, & Physical Data Models
- What is OLAP (Online Analytical Processing): Cube, Operations & Types
- What is MOLAP? Architecture, Advantages, Example, Tools
- OLTP vs OLAP: What’s the Difference?
- What is Dimensional Model in Data Warehouse?
- Star and SnowFlake Schema in Data Warehousing
- Data Mart Tutorial: What is Data Mart, Types & Example
- Data Warehouse vs Data Mart: Know the Difference
- What is Data Lake? It’s Architecture
- Data Lake vs Data Warehouse: What’s the Difference?
- What is Business Intelligence? Definition & Example
- Data Mining Tutorial: Process, Techniques, Tools, EXAMPLES
- DataStage Tutorial: Beginner’s Training
Section 3- Must Know!
- Difference between Data Mining and Data Warehouse
- Difference Between Fact Table and Dimension Table
- Difference between Information and Data
- Teradata Tutorial: Learn Basics for Beginners
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