Data Warehousing - Self-Pacededureka
$ 170 - (Rs 11,486)
What you'll learn on the course
1. Introduction to Data Warehouse
Learning Objectives - Discussing about the basic concepts of a data warehouse and why it is needed. Difference between an operational system and an analytical system, Datamarts. Approaches to build a data warehouse.
1. What is a data warehouse? - Definition and explanation of the four terms - subject oriented, integrated, non volatile and time variant
5. ODS - Operational Data Store - Definition and explanation of 4 terms - Subject oriented, Integrated, Current, Volatile, Detailed6. Benefits of ODS 7. Design approach - Top down approach, bottom up approach, Federated 2. Dimension and Fact
Learning Objectives - Learning what a dimension and a fact is, the different types of dimensions and facts. Reporting concept of Hierarchy.
1. Dimensions and facts - What are dimensions and facts?
Learning Objectives - Organizing data in multiple tables. Understanding normalization and its different forms. Learning what is a schema and the different types of schemas along with meta data.
Learning Objectives - Understanding principles of requirement gathering to build a warehouse and dimensional modeling.
1. Requirement gathering
2. Principles of dimensional modelling
3. Modeling - ER diagrams5. ETL in Detail
Learning Objectives - Understanding where will the data come from and how will the data come and Populating the warehouse.Learning concepts of Extracting data, Transforming data and Loading the data into different tables.
1. ETL Concept - Architectural components - like Source, Staging, Atomic, Dimension
2. Transformation - Data Validation, Data Accuracy, Data Type Conversion, Business Rule Application
3. Data Loading techniques.6. Project
Learning Objectives - Implementing a data warehouse Project.
Topics - Discuss a project, its problem statement, probable solutions, and implement one solution.