DATA WAREHOUSING AND DATA MART

Data Warehousing and Data Mart

Data Warehousing and Data Mart

Introduction

None of the data mart resembles with any other data mart. However, it is possible to coordinate the data of various departments. Data mart of a specific department is completely focused on individual needs, requirements and desires. Data in data mart is highly indexed but is not suitable to support huge data as it is designed for a particular department.

Firstly, Data mart represents the programs, data, software and hardware of a specific department. For example, there is separate data mart for finance, production, marketing and sales department (Vassiliadis, 1998, 32-44).

Data warehousing is not limited to a department of office. It represents the database of a complete corporate organization. Subject areas of data warehousing includes all corporate subject areas of corporate data model. Data warehousing is neither bounded to have relations between subject areas of departments nor with subject areas of corporation. Detailed data is stored in the database of data warehousing unlike data mart which stores only aggregated or summarized data. Data in the data warehouse is indexed lightly as it has to manage large volume of data. It would be wise to say that there is very little difference in data structure and content of data mart and data warehouse.

Comparison

Patterns of Data Mart and Data Warehouse Development

In the beginning, there were only the islands of information: the operational data stores and legacy systems that needed enterprise-wide integration; and the data warehouse: the solution to the problem of integration of diverse and often redundant corporate information assets. Data marts were not a part of the vision. Soon though, it was clear that the vision was too sweeping. It is too difficult, too costly, too impolitic, and requires too long a development period, for many organizations to directly implement a data warehouse (Pedersen, Jensen, 1999, 55-88).

A data mart, on the other hand, is a decision support system incorporating a subset of the enterprise's data focused on specific functions or activities of the enterprise. Data marts have specific business-related purposes such as measuring the impact of marketing promotions, or measuring and forecasting sales performance, or measuring the impact of new product introductions on company profits, or measuring and forecasting the performance of a new company division. Data Marts are specific business-related software applications.

Data marts may incorporate substantial data, even hundreds of gigabytes, but they contain much less data than would a data warehouse developed for the same company. Also since data marts are focused on relatively specific business purposes, system planning and requirements analysis are much more manageable processes, and consequently design, implementation, testing and installation are all much less costly than for data warehouses.

In brief, data marts can be delivered in a matter of months, and for hundreds of thousands, rather than millions of dollars. That defines them as within the range of divisional or departmental budgets, rather than as projects needing enterprise level funding. And that brings up politics or project ...