Data marts "" ever heard of them? Not many people have, but they are essential to the data warehouse that is a key part of most businesses that have vast amounts of customer, employee or product data to store and manage. There are a few different types of data marts, namely, The Star Schema, the Snowflake Schema and the Data or OLAP Cube. Each has their own function and purpose within the data warehouse design and functionality parameters and depending on the type of data you have and the type of business you are, each could be beneficial.
What is the technical definition of a data mart? Through the business intelligence framework, a data mart provides primary access to data stored in a data warehouse or operational data store. It is a subset of data, specifically focused on a business function or set of related business functions. As a repository of centralized, cleansed, standardized, transformed and integrated historical data, the data warehouse provides an organizational view of the business from a data perspective. The problem with data warehouses? It"s very hard to access or report on the data within it. If you need help, it"s a good idea to consider
software projects outsourcing.
There"s three key things you should know about a the data in a data warehouse:
"It"s organized by subject area
"The data is historical and can be accessed by date
"It represents the organization as a whole
In fact, its very similar to an operational data store (ODS), but the data in an ODS is not historical. It"s a much more simplistic setup and does not provide the same functionality. If data organized by date is important to you, a data mart is critical.
You"ll have easy access to data in the warehouse because the data in the data mart is customized to the business unit and based on your business requirements; it will truly be a one of kind system, addressing the important issues as it pertains to your business. If you need to see data reporting, trending, analysis and presentation, the data mart will be your best friend.
What are the specific types of data marts and how do they function? As mentioned earlier, there are three of them. Here is more information on each:
Star Schema Data Marts
As the most frequently used type of data mart, the star schema features a fact table and a set of dimension tables. The data mart is distinguished by the relationships between the two sets. A fact table is a set of metrics generated that relates to a specific business process. A dimension table is a set of elements that describe the events of metrics in the fact table. Star schema data marts are simple and very cost effective to deploy and provide multidimensional functionality within a relational database. Its design lends itself best to trend and historical reporting and is supported by most DBMSs including SQL Server, UDB and Oracle. If your business uses these types of software and could benefit from a fact and dimension data relationship setup, take a closer look at the Star Schema. It will bring clarity and insight into your data and help to show trends and patterns as well as business opportunities and deficiencies.
Snowflake Schema Data Marts
Have massive amounts of data to organize? A snowflake schema data mart is a star schema with dimension tables that have been normalized. This type of data mart works best in situations where dimension tables are too large or too sparse. A snowflake schema will have the fact table; however, the dimension tables may have parent tables that they are related to. This design enables the efficient use of storage, as there is a significant reduction in data redundancy. If you are a large e-store or retail store and have millions or even billions of data pieces, this may be a good option for you. It will bring the ultimate level of transparency and insight and bring much needed organization to the data sets. Keep in mind though that software maintenance is more time consuming.
Data or OLAP Cubes
Do you need to slice and dice and find patterns in your data? A data or OLAP cube will work very well. Optimized to report on data from different perspectives, it can be customized to your specific needs. Working within analytics, trending and historical reporting, it is a multidimensional database that is designed to support all types of reporting needs. It is organized into measures and dimensions. A data or OLAP cube is ideal for solutions that require efficient reporting with complex business requirements. Do you use Business Objects, Cognos, Hyperion or SQL Server Analysis Services (SSAS)? Then an OLAP Cube may work well. One thing to note: the design, maintenance and processing of the cube should is time intensive.
In summary, Data Marts serve important roles in the overall software architecture for data base management and Accelerance partners all over the globe are skilled in designing this type of software. If you require assistance with your next project,
software outsourcing might turn out to be an excellent solution.
