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Big Data and Unstructured Data: Farewell to Data Trapped By Words?
Unstructured data is information that isn’t stored according to a pre-defined data model. Unstructured data is text-heavy and the information contained in it has proven to be challenging for computer software to analyze, unlock and to then be able to use and act on. Unlike data stored according to database or XML schemas, unstructured data is free-flowing and highly irregular in format. Examples of unstructured data include email messages, PowerPoints, Word documents, instant messages, and ‘tweets’. Unstructured data also includes non-textual data like videos, JPEG images, and MP3 audio files.
The two techniques that have had some success in gradually opening up bits of the unstructured data world to machine analysis are XML and NoSQL databases. These technologies try to apply meaning and organization to multi-structured datasets. The TABB group estimates that Machine-Readable Data (MRD) will generate $75 million in 2013 revenue, and that amount is expected to increase significantly in the future. Market analysts and money managers are expected to leap at the opportunity of ‘instant’ analysis of market reports. 60 percent of the MRD market is now being purchased by hedge funds and traditional asset managers.
Paul Rowady, analyst at the TABB group, wrote that “conversion of unstructured data into an expanding universe of structured data will soon become ubiquitous. Trading strategies, risk analytics, fraud detection, and all sorts of decision support in global capital markets will eventually incorporate this converted data. Though early use cases of machine-readable data have already made headlines, we are most certainly only at the beginning of this journey.”
Rowady said that “the sheer volume of data we’re able to process indicates how small a subset economic events and corporate news is within the MRD category. This growing segment of the ‘big data’ megatrend will eventually include nearly all new data created, including audio and video.”
