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Published 12/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 888.63 MB | Duration: 2h 13m
Data Warehouse
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 888.63 MB | Duration: 2h 13m
Data Warehouse
What you'll learn
We really hope this course will help you with your career immensely and take you to the next level
Assessment questionnaires are included at appropriate points to test your knowledge
Important sessions of this course are Transactional vs Analytical Processing, ETL
Data Warehouse Architecture, Data Mart, Data Warehouse Schema and SCDs
Requirements
You need to have Basic knowledge on RDBMS Concepts and SQL
Description
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. In this course you will learn everything about the Data warehouse. 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 architecture is made up of tiers. The top tier is the front-end client that presents results through reporting, analysis, and data mining tools. The middle tier consists of the analytics engine that is used to access and analyze the data. The bottom tier of the architecture is the database server, where data is loaded and stored. Data is stored in two different types of ways: 1) data that is accessed frequently is stored in very fast storage (like SSD drives) and 2) data that is infrequently accessed is stored in a cheap object store, like Amazon S3. The data warehouse will automatically make sure that frequently accessed data is moved into the "fast" storage so query speed is optimized.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.Here is what you'll learn
ata Warehouse BasicsHistory of Data WarehouseOLTP & OLAPIntroduction to ETLExtraction, Transformation and Load data in ETLTypes of TransformationData Warehouse ArchitectureData Warehouse Architectures based on layers and TiresData MartStoring Data in Data WarehouseDimension Tables and Fact TablesDimension and Fact table with ExampleDWH SchemaStar SchemaSnowflake SchemaFact Constellation SchemaSCD IntroductionSCD Type 0 and 1SCD Type 2SCD Type 3SCD type 4SCD Type6ETL ToolsScheduling the ToolsReporting ToolsOverview
Section 1: Introduction
Lecture 1 Introduction to Data Warehouse
Lecture 2 Transactional vs Analytical Processing
Lecture 3 What is Data warehouse?
Lecture 4 History of Data Warehouse
Lecture 5 OLTP & OLAP
Lecture 6 Introduction to ETL
Lecture 7 Extraction in ETL
Lecture 8 Transformation Introduction
Lecture 9 Types of Transformation
Lecture 10 Load Data
Lecture 11 Data Warehouse Architecture Introduction
Lecture 12 Data Warehouse Architectures based on layers
Lecture 13 Data Warehouse Architecture based on Tiers
Lecture 14 What is Data Mart?
Lecture 15 Storing Data in Data Warehouse
Lecture 16 Dimension Tables and Fact Tables
Lecture 17 Dimension and Fact table with Example
Lecture 18 Introduction To Data Warehouse Schema
Lecture 19 Star Schema
Lecture 20 Snowflake Schema
Lecture 21 Fact Constellation Schema
Lecture 22 SCD Introduction
Lecture 23 SCD type 0 and 1
Lecture 24 SCD type 2
Lecture 25 SCD Type 3
Lecture 26 SCD type 4
Lecture 27 SCD Type6
Lecture 28 ETL tools
Lecture 29 Scheduling the Tools
Lecture 30 Reporting Tools
This course is for Students, Professionals or Anyone who needs upgrade their knowledge in Data Warehouse
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