by Angela Guess
The four Vs of Big Data are volume, velocity, variety, and value. Amir Halfon recently wrote an article regarding how to handle the variety of Big Data. He writes, “Variety refers to various degrees of structure (or lack thereof) within the source data. While much attention has been given to loosely-structured Web data, whether sourced from the Web itself (social media, etc.), or from Web server logs, I’d like to turn to the topic of unstructured data within the financial institution’s firewall and focus on the challenge of linking diverse data with various levels of structure, rather than discussing the storage and analysis of unstructured data as a standalone problem.”
He continues, “Let’s start with a couple of examples. Financial institutions are under pressure to retain all interaction records related to transactions, such as phone calls, emails, instant messages, etc. Recently, more attention has been given to the linkage between these records and the corresponding transactions handled by trade capture systems, order management systems, and the like. There is growing realization that regulations such as Dodd-Frank will require this linkage to be not only established, but readily available for on-demand reporting. Aside from regulatory compliance, interaction records can also be quite useful for rogue trading and other fraud detection analysis once effectively linked to transactional data.”
photo credit: JimboRocks
