As big data becomes an increasingly important part of the computer science and business worlds, organizations know that they must continue to refine their analytics methods. While it is still early to determine what exactly is needed to produce the best results, it appears that data preparation is crucial to all analytics projects. A recent article in Network World examines why it is so vital.
A popular saying in IT is "garbage in, garbage out," which refers to a computer's inability to separate the wheat from the chaff when it comes to processing data. Thus, data management best practices require a human element to prepare information for analysis to ensure the best possible results. This can be a time-consuming process due to the diverse sources that some projects require.
Depending on the nature and scope of each project, relevant data can come in any number of file formats, including from outdated legacy systems and even non-digital files. Before a data management undertaking can really begin, all that information needs to be identified, extracted, cleaned up and transformed to a single format and uploaded to a destination where it can be easily accessed and analyzed.
Proper preparation weeds out unnecessary information and avoids duplication when dealing with multiple, sometimes overlapping sources. Even if it takes extra effort and delays a project's start date, the long-term benefits of data preparation will be well worth your time and will prevent you from having to wade through a mess of data later.