DIFFERENCESTerms And Technology

Difference between Data Warehouse and Data Mart with table

We explain the difference between Data Warehouse and Data Mart with table. Data analysis is one of the most sought after needs by any organization. Analysis requirements gather speed and momentum, especially if your organization grows over a period that spans multiple units and divisions.

At any time, an entity would like to evaluate data to understand and / or make decisions related to the entire unit or a subdivision. Data Warehouse and Data Mart are the preferred tools used in such scenarios. Data Warehouse and Data Mart perform the same task, viz. However, data analysis has subtle differences, especially when it comes to the users being served.

The main difference between Data Warehouse and Data Mart is that Data Warehouse is a setup to analyze data at the general organizational level, while Data Mart is a subset of Data Warehouse and is used to analyze data for specific domains / users.

However, the above is not the only difference. A comparison between both terms on certain parameters can shed light on subtle aspects:

Comparison table between Data Warehouse and Data Mart (in tabular form)

Comparison Parameter

Sense System used to store, retrieve, manage, report and analyze large amounts of any type of data. Data Mart is a subtype or subset of Data Warehouse
Purpose For data analysis It is used for data analysis, but it is directed or designed for certain groups or users.
Implementation perspective Longer time due to complex nature and ability to handle big data Less time due to focusing only on specific areas
Thematic area It is not focused on any specific domain or topic, it is used for the whole business as a whole. It is topic-oriented, for example, data analysis related to the human resources department
The amount of data Yes No, because it is specific to some users.
Macro level or micro level Used for the entire organization Focused only for certain users, therefore it can be considered suitable at a micro level
Which is more useful? It depends on the specific needs, but in general it can be considered more useful as it provides the information of the entire company (including all departments) It depends on the specific needs, but in general it can be considered less useful as it is restricted to some domains / user groups

What is Data Warehouse?

Data Warehouse is the most preferred system for managing large data. The data warehouse can be called as a powerful tool for analyzing data. Data Warehouse is an informational setup for scrutinizing, investigating and analyzing voluminous and voluminous volumes of data that can be historical or current.

Data Warehouse works with the philosophy of collecting data from numerous sources or applications, processing it, and finally performing analysis. This process helps generate numerous customized reports and summaries for management decision making. One of the cool features of Data Warehouse is that stored data is not erased when new data is added.

Data Warehouse is a boon for an organization when it comes to data analytics. The data warehouse is used primarily to report, compress, analyze, investigate, integrate, and summarize data to make data-related judgments and determinations. Data Warehouse adopts sophisticated techniques to enable quick search and accurate analysis.

Data Warehouse has some disadvantages that prevent certain organizations from implementing it. Some of the main disadvantages include expensive implementation and ongoing maintenance. Also, if the data involved is too complex and voluminous, the processing time can be considerably reduced.

What is Data Mart?

Data Mart is a part (type) of Data Warehouse. In simple terms, Data Mart is the access layer of a data warehousing environment, used to distribute data to specific users. Data Mart can be thought of as a subset (and also an important one) of the Data Warehouse.

Data Mart is topic or goal oriented, which means it is designed to meet the needs of particular groups or departments within an organization. For example, your organization’s human resources division may be interested in analyzing retention and resignation trend data. In such cases, the Data Mart will help generate the necessary results.

Data Mart is simple and easy to manage and has a lower cost. Data Mart uses limited amounts of data and processes it quickly. As Data Mart focuses only on certain specific users / industries, it is a blessing to evaluate data at a micro level or specific lines of business.

Data Mart has some shortcomings. For example, Data Mart can extract data only from limited / few sources, can store only a limited amount of data, and will have certain size limitations. Also, as the organization grows, there may be a tendency to create too many Data Marts, which can be a complex process. Data Mart cannot be considered an enterprise platform for data analytics solutions.

Main differences

  • Data Warehouse is a system for managing and analyzing large amounts of data. Data Mart is a type of data warehouse.
  • Data Warehouse manages the data of all departments / companies as a whole. Data Mart focuses on specific domains / users / groups.
  • Data warehouse design and implementation is complex and time consuming. Data Mart design and implementation is easy and requires less time.
  • The data warehouse can take large amounts of data, but the processing will take longer. Data Mart only takes less data to process, but it will process quickly.
  • The size range of the datastore is quite large (maybe more than 1TB). The size of the Data Mart is small (GB only).
  • The data warehouse is most useful for an organization as a whole. Data Mart is most useful for a single domain / department.

Final Thought

Data Warehouse and Data Mart are quite similar in their data management capabilities. Both offer multiple but different sets of benefits and have certain disadvantages. Data Warehouse and Data Mart serve the same purpose (that is, data analysis) but serve different groups of users.

Data Warehouse will assist at the organizational level, while Data Mart will provide support at the departmental level. Therefore, it is important to assess these aspects and also individual / organizational / divisional needs before deciding to adopt a Data Warehouse or Data Mart.

A prudent option would be to start with the Data Warehouse and then move on to the Data Mart if there is a need for a specific topic. Thorough hands-on knowledge and advice, especially from data management specialists, is suggested to reap the full benefits of Data Warehouse or Data Mart implementation.

The most important focal point that should always be kept in perspective is whether the implemented system will serve the ultimate purpose of the organization.

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