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What is a Data Mart? - Design, Types & Example

Instructor: Martin Gibbs

Martin has 16 years experience in Human Resources Information Systems and has a PhD in Information Technology Management. He is an adjunct professor of computer science and computer programming.

Sometimes it's easier to shop in a small store, rather than a super-sized grocery store. This lesson will cover data marts (the small store of the data world), describe how they are designed, and give examples.

Why Shop at the Megastore?

Databases have become HUGE. In corporate settings especially, they can be overwhelming. As with a grocery store, sometimes bigger isn't always better. It's great to have every last item in one store, but sometimes we need a place to go that isn't so huge. Enter the data mart (the Quick-E mart of the warehousing world).

A data mart is a simple section of the data warehouse that delivers a single functional data set. In a human resources database, we could create data marts for Employees, Benefits, or Payroll to name a few.

Dependent Data Marts

While a data mart is a smaller subset of data, the broader data warehouse is like the mega-mart. It houses ALL of the data. Data marts can be built off of a line of business (for example Finance or Marketing), but you can also build them based on specific departments. Think of a large retail organization. Data marts might exist for the major lines of business, but other marts could be designed for specific products. Examples include seasonal products, lawn and garden, or toys.

Implementing a Data Mart

Implementing a data mart includes the concepts of design, build, data transfer, and data access.

Design

Before creating a data mart, you need a solid design. The basic design steps for a data mart include the following:

  • Requirements gathering: Both technical and business requirements need to be captured and documented.
  • Identify the data source(s)
  • Determine the subset of data (Will you bring in ALL employee information or a subset of the information?)
  • Design the physical and logical layout of the data mart

Logical layout means the database schema. That is, the tables and fields should match what is in the larger warehouse.

Build

Once the design is set, you can start to build the data mart. You'll need to create the tables, fields, indexes, and access controls in the data mart.

Data Transfer

How do you populate the mart? This is an important step because the data needs to get to the data mart. And, it needs to be correct! It is easier if you've created the same structure in both warehouse and mart.

For example, the Employee data transfer setup could look like the following table. Fields from the warehouse and the mart are detailed.

Data Warehouse Data Mart
Employee ID Employee ID
SSN Last 4 SSN
First Name, Last Name, MI Last Name + First Name + MI
Rate of Pay 0 (hard-coded)
Status First 3 characters of status value

Note how some fields are a little different. Even though we have the same data, sometimes we need to scrub it or tweak it or maybe just make it user-friendly. The data mart is a great tool for this.

You'll also need to determine a frequency for transferring data. It can be any time interval such as daily or weekly. Also, data is typically over-written each time so that the data in the mart and warehouse is clean.

Data Access

This is where it all comes together. Now that we designed the structure, built the mart, and generated a data transfer protocol, we can start using the data!

Some powerful tools you can develop to further boost end user productivity:

  • Create a layer between the end user and the mart, which translates database names into business terms. For example: R_Employee_Var_ID becomes Employee_ID
  • Setup saved queries, summary tables, counts, and measures. These could include the average cost of orders, total employee counts, or open calls. Summary data is very useful to end users as they often need to report only this type of information.

Users will have tools to query the database (Business Objects, Microsoft SQL Query studio, even Excel).

The following graphic captures the full design process of a data mart.

Data Mart Design

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