The concept that, more than any other variable, has put the “big” in Big Data, has to be the notion of uncontexted, unstructured, or non-traditional data and the potential it represents. The term “non-traditional” when applied to data generally refers to data that does not easily lend itself to be captured in spreadsheets, tables, or relational databases. Some examples of this type of data include non-relational database data, such as documents, email, instant messaging(IM)/texting, and sensor data, and “signal” data like blogs and social media.
But non-traditional data typically can’t be captured with the same old tools or analyzed with the same old methods. Applying MDM to non-traditional data raises a different set of challenges than when dealing with traditional data. Although you will be asking some of the same questions as you would with traditional data, you may need to use a different approach or involve a completely new perspective to realize Big Data’s potential. Continue reading 5 Best Practices for Applying MDM to Non-Traditional Data