Big data is growing bigger every day, but it’s still a very new trend for the business and IT worlds. Organizations are working to develop new ways of taking advantage of terabytes of available data, and in many cases it’s too early to determine which are the most effective methods. One aspect whose importance is often overlooked but that is a necessary part of any successful analytics project is data preparation.

Data can be hard to analyze if it is still raw and unpolished, especially when it comes from different sources, and certainly not all information that is available is necessarily useful. Attempting to soldier on without cleaning data up first will inevitably produce skewered and inaccurate results. In the field of computer science, the saying “garbage in, garbage out” reflects the inability of automated processes to separate the wheat from the chaff.

On any given analytics project, companies can use information generated specifically for that purpose or from automated sources. The data can come in any number of file formats or it may even be in physical files or come from outdated legacy systems. A comprehensive ETL architecture can comb all those sources, select only the relevant data and bring it together in a single destination, where it can be easily analyzed.

Management Information Analysis‘ ETL Plus* service allows for each part of the process to be customized to meet the specific requirements of each organization and project. We can transform vital information from very disparate sources and ensure that it is primed for analysis by eliminating duplicate and irrelevant data.