Our Blog

The Necessity of Data Mart in Data Analytics

We all know data is power. When it comes to using power, how you use your power is very important, and abusing or wasting that power is not acceptable in terms of administration or users. The global economy has become a perpetual motion machine of data; consuming, processing, and producing even more quantities of it. Additionally, digital technologies trafficking in data now enable, and in some cases replace, traditional trade in goods and services.

When we talk about modern reports and reporting tools, expectations are high. Interactivity and fast refreshing data are not just demanded, it’s a necessity. In which case, using raw tables or a prime data source will not be able to provide better speeds or feasibility. Some reports require modified data types, unpivoted data, column-wise data amongst many others regularly. And the solution for this challenge is found by developing diverse Data Marts on a demand basis. This helps faster reporting by not using custom or complex queries in reporting.

In a market dominated by big data and analytics, Data Marts are one of the key factors in efficiently transforming information into insights. Data warehouses typically deal with large data sets, but data analysis requires easy-to-find and readily available data. Therefore, the need to perform complex queries in order to access the data needed for reporting is unnecessary with the use of a Data Mart.

A Data Mart is focused on a single functional area of an organization and contains a subset of data stored in a Data Warehouse. A Data Mart is a condensed version of Data Warehouse and is designed to be used by specific departments, units or a set of users in an organization. E.g., Marketing, Sales, Human Resources or Finance departments, and is often controlled by a single department in an organization.

Data Marts and Data Warehouses are both highly structured repositories where data is stored and managed until it is needed. However, they differ in terms of the scope of data stored: data warehouses are built to serve as the central store of data for the entire business, whereas a Data Mart fulfills the request of a specific division or business function. Due to the fact that a data warehouse contains data for the entire company, it is best practice to have strict control who can access it. Additionally, querying the data you need in a data warehouse is an incredibly difficult task for businesses. Therefore, the primary purpose of a Data Mart is to isolate or partition smaller sets of data to provide easier data access to end consumers.

Users can share their requirements and the Database team can provide the source by entering the necessary logics and rules into a Data Mart. Thus, hitting raw tables reduce which in turn improves database performance and smart warehousing. Therefore, you don’t need to think about your main tables but rather focus on the optimization.




Munshi Muntasir Islam

Munshi is a Senior Consultant – Analytics at VS ONE Bangladesh. He started his career in 2015 in the telecommunication industry in Bangladesh and focused on analytics and data science in 2018.

With a degree in Electronics and Telecommunication Engineering, Munshi found that his passion was in data analytics and  switched tracks to obtain a Professional Certification on Data analyst & Data Scientist.