10-04-2017, 09:07 PM
data warehousing ashok kumar notes
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data and are used for creating analytical reports for knowledge workers throughout the enterprise. Examples of reports could range from annual and quarterly comparisons and trends to detailed daily sales analyses.
The data stored in the warehouse is uploaded from the operational systems (such as marketing, sales, etc., shown in the figure to the right). The data may pass through an operational data store for additional operations before it is used in the DW for reporting.
This Data Warehousing site aims to help people get a good high-level understanding of what it takes to implement a successful data warehouse project. A lot of the information is from my personal experience as a business intelligence professional, both as a client and as a vendor.
This site is divided into six main areas:
- Tools: The selection of business intelligence tools and the selection of the data warehousing team. Tools covered are:
Database, Hardware
ETL (Extraction, Transformation, and Loading)
OLAP
Reporting
Metadata
- Steps: This selection contains the typical milestones for a data warehousing project, from requirement gathering, query optimization, to production rollout and beyond. I also offer my observations on the data warehousing field.
- Business Intelligence: Business intelligence is closely related to data warehousing. This section discusses business intelligence, as well as the relationship between business intelligence and data warehousing.
- Concepts: This section discusses several concepts particular to the data warehousing field. Topics include:
Dimensional Data Model
Star Schema
Snowflake Schema
Slowly Changing Dimension
Conceptual Data Model
Logical Data Model
Physical Data Model
Conceptual, Logical, and Physical Data Model
Data Integrity
What is OLAP
MOLAP, ROLAP, and HOLAP
Bill Inmon vs. Ralph Kimball
- Business Intelligence Conferences: Lists upcoming conferences in the business intelligence / data warehousing industry.
- Glossary: A glossary of common data warehousing terms.