B.Sc. CSIT 7th Semester Data Warehousing and Data Mining

Architecture of data warehouse

  • Three-tier data warehouse architecture is the most widely used architecture of data warehouse as it produces a well-organized data flow from raw information to valuable insights. 
  •  It consists of the Top, Middle and Bottom Tier. 
  •  The top tier is the front-end client tools that presents results through reporting, analysis, and data mining tools. 
  • The middle tier consists of the analytics engine that is used to access and analyse the data. 
  •  The bottom tier of the architecture is the database server, where data is loaded and stored.
Architecture of data warehouse

Bottom Tier:

  • The database of the data warehouse servers as the bottom tier. 
  •  It is usually a relational database system. 
  • Data is cleansed, transformed, and loaded into this layer using back-end tools.

Middle Tier:

  • The middle tier in data warehouse is an OLAP server which is implemented using either ROLAP or MOLAP or HOLAP model. –
  • For a user, this application tier presents an abstracted view of the database. 
  •  This layer also acts as a mediator between the end-user and the database.

Top Tier:

  • The top tier is a front-end client layer. 
  • It is the tools and API that you connect and get data out from the data warehouse. 
  • It could be query tools, reporting tools, managed query tools, Analysis tools and Data mining tools.


  • Data warehouse systems use back-end tools and utilities to populate and refresh their data . These tools and utilities include the following functions: 
  •  Data extraction, which typically gathers data from multiple, heterogeneous, and external sources. 
  •  Data cleaning, which detects errors in the data and rectifies them when possible.
  • Data transformation, which converts data from legacy or host format to warehouse format. 
  • Load, which sorts, summarizes, consolidates, computes views, checks integrity, and builds indices and partitions. 
  •  Refresh, which propagates the updates from the data sources to the warehouse.
Architecture of data warehouse

Also read conceptual modelling of data warehouse.

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Karina Shakya