Data Integration Categories

by Katherine VasilegaOctober 4, 2010

There are three major data categories to consider when carrying out data integration initiatives. They require a clear understanding to help find a proper data integration solution. Here is a brief description of each category.

1. Master Data. Also called reference data, master data is any information that is considered to play a key role in the business. Master data may include information about customers, products, employees, locations, inventory, suppliers, and more. Master data is stored in the Data Warehouse.

2. Operational Transaction Data. This data includes the information about the activities, such as purchases, call details, claims, transactions, and so on. This data is stored in the Operational Data Store and is considered low-level data with limited history that is captured “real time” or “near real time” as opposed to the much greater volumes of master data.

3. Decision Support Data.
This data category includes historic data used in strategic and tactical analyses. Trends, patterns, data mining, and multi-dimensional analytics can then be used in Decision Support systems that are able to provide predicted outcomes from different scenarios and strategies, so answering “what if?” questions.

All three data types require similar processes, as data must be collected, cleaned, integrated, and populated into the repository. In addition, the three forms of data share many of the same data integration technologies: ETL, hardware, software, applications.

Whether you create a distinct data integration solution for each data type, or a single data integration solution for all three types, you have to study what data integration vendors are offering and choose the best technology to fit your needs.