Introduction to Data Warehouse

A Data warehouse is a database that is used for data analysis and reporting. It is a central repository for all the data that is needed for reporting and analysis. Data and analytics have become indispensable to businesses to stay competitive. Business users rely on reports, dashboards, and analytics tools to extract insights from their data, monitor business performance, and support decision making. Data warehouses power these reports, dashboards, and analytics tools by storing data efficiently to minimize the input and output (I/O) of data and deliver query results quickly to hundreds and thousands of users concurrently.

A data warehouse may contain multiple databases. Within each database, data is organized into tables and columns. Within each column, you can define a description of the data, such as integer, data field, or string. Tables can be organized inside of schemas, which you can think of as folders. When data is ingested, it is stored in various tables described by the schema. Query tools use the schema to determine which data tables to access and analyze.

A data warehouse is specially designed for data analytics, which involves reading large amounts of data to understand relationships and trends across the data. A database is used to capture and store data, such as recording details of a transaction.

The course is a right blend of concepts with right examples for making the topics easier which includes

• 2+ hours of on demand videos

• Clarifications through community

• Understand everything step by step from the absolute basics to the advanced topics

Here is what you'll learn:

• What is a Data Warehouse?

• What is the need for Data Warehouse?

• History of Data Warehouse

• OLTP & OLAP

• Introduction to ETL

• Extraction, Transformation and Load data in ETL

• Types of Transformation

• Data Warehouse Architecture

• Data Warehouse Architectures based on layers and Tires

• Data Mart

• Storing Data in Data Warehouse

• Dimension Tables and Fact Tables

• Dimension and Fact table with Example

• Data Warehouse Schema and Types

• Slowly Changing Dimensions Introduction and Types

• ETL Tools

• Scheduling the Tools

• Reporting Tools