What is a Datamart? Definition of a subset of the Data Warehouse
Find out what a Datamart is and what it can do for a business. This subset of the Data Warehouse is intended for professions. This tool is at the beginning of Big Data.
Data warehouses are inextricably linked to Big Data. It is in these places that companies, suppliers store files and their metadata in order to archive or process them. Usually known as Data Warehouse, there are specific formats of data warehouses , subsets. Among these is the Datamart.
Datamart vs data warehouse
A Datamart is therefore a sub-element of the Data Warehouse that can be translated into French by data store or data counter. Here the goal is not to collect data before sorting it (the definition of the Data Warehouse), but to organize it according to business uses or targeted areas. They will be used by user groups in the company.
The Datamart brings together a set of organized, targeted, aggregated and grouped data in order to meet the needs of the trades. Technically, it is created from a relational database operated from the SQL computer language and stored physically on a hard drive through a database management system.
Datamart definition: two schools of thought
Its principles and operation are theorized by two computer scientists: Bill Inmon and Ralph Kimball.
Bill Inmon, considered by many to be the creator of the Data Warehouse, this researcher has written more than 40 books and more than 1,000 articles on this subject. It defines Datamart as a data flow from the Data Warehouse. It gathers in a functional way the specialized data, aggregated for a particular trade. In this approach, it is not at the heart of the data warehouse, but on the periphery of it.
Ralph Kimball, also a computer scientist and business manager who has written numerous books on datawarehousing. According to him, the Datamart is a subset of the Data Warehouse composed of detailed or aggregated tables, linked together. The idea is to make it accessible, fast and representative of an activity in a company. According to Kimball, the Datamart are the Data Warehouse.
These two conceptions of Datamart converge towards the same appreciation of this item. It is an extract from all the data of a company, it contains only what is necessary . Unnecessary data is removed and historization is performed according to the user’s request. Thus the trades are not disturbed by parasitic or contiguous data. Two models of use of Datamart prevail: the interrogation of stocks (or the history of commercial activity), or activity in flow (direct orders).
The architecture designed on a relational database and the need to silo the data facilitates the speed of access, but locks the possibilities. An unusual request made from a database query software, for example a reporting tool, will not give the expected result unless access to other parts of the Data Warehouse is modified.
Several uses of this type of database are possible. Three professions are particularly concerned: marketing, commerce and human resources.
Datamart marketing and sales
This type of relational database focuses on the needs of marketing managers whose job is to identify prospects and target customers. With such a tool within their reach, they can consult all of the contacts registered with the company. The names, first names, telephone numbers, physical addresses and emails are some of the information available. With an associated reporting tool, he can quickly know who he has contacted, whether he has successfully sold him a product, whether he is satisfied, etc. All of this can be linked to the impact of behavior on the company’s turnover.
Datamart Human Resources
Here we use the employee information to record arrivals and departures of employees, the average age of employees, professions represented, seniority in the company, compensation, etc . This provides statistics and reports to assist in hiring or firing decisions.
This time, it is a question of providing business intelligence concerning the financial and administrative health of the company. The overall turnover, by sector, as well as the costs are analyzed. Likewise, audit elements such as invoices, their origins and purchase orders. We can identify the arrears, the profits, the salary cost of the company according to the data flows used.
Datamart VS Cube
New Business Intelligence users often confuse Datamart and Cube. They are easily understood, these are two elements relating to business applications within a Data Warehouse. Only, the first is a subset of this infrastructure and collects all the data concerning an activity. The Cube allows you to make requests in order to answer specific questions from the trades. How old is a working population? what is the turnover rate? This is what this tool will be used for.