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Data warehousing

Data Warehousing (DW) is process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.

It is a blend of technologies and components which aids the strategic use of data. It is electronic storage of a large amount of information by a business which is designed for query and analysis instead of transaction processing. It is a process of transforming data into information and making it available to users in a timely manner to make a difference.

Data Warehouse Life Cycle Design

  • Requirements gathering
  • Requirements analysis
  • High level design (HLD)
  • Low level design (LLD)
  • Development – Automating scripts
  • Testing
  • User Acceptance Testing (UAT)
  • Project release or deployment
  • Warranty support

Steps to Implement Data Warehouse

Enterprise strategy

  • Identifyng technical including current architecture and tools.
  • identifyng facts, dimensions, and attributes.

Phased delivery

  • Datawarehouse implementation should be phased based on subject areas.
  • Related business entities like booking and billing should be first implemented.

Iterative Prototyping

  • Data Warehousing Implementation includes Iterative Prototyping.
  • Datawarehouse should be developed and tested iteratively.