Firms looking to deploy data analytics are finding many areas full of unstructured data that are ripe for organization and deriving new insights
More firms and providers in the financial industry are trying to harness the value of data analytics and apply it to their data management. One facet of reference data is emerging though, as a giant "goldmine" for the application of data analytics, and that is unstructured data.
This type of data is probably nothing new, as Australian data-development expert Leif Hanlen describes it: "50 million Word documents saved over the last 10 years and put in a box" ... cannot automatically "turn out to be as good as the accounting machinery they have been using since the 1970s." Hanlen is a business development executive at the Commonwealth Scientific Industrial Research Organization (CSIRO), a digital operations consultancy, backed by Australian national and state governments, and CSIRO's Data61 subsidiary.
Unstructured data has started to bubble up as a matter of concern and interest in Inside Reference Data's coverage this year. In March, ISITC executive Jeff Zoller pointed to unstructured data about investment behavior and patterns, as well as industry analysts' commentary, and social and economic behavior, potentially supporting the disruption of data-management technology. In May, MUFG Canada Branch chief information and operations officer Ron Lee, speaking about how his firm is consolidating systems, noted this effort would increase the capability to work with unstructured databases.
The task for analytics of unstructured data is not to build a brand new goldmine, but to extract elements of information from that unstructured data
Leif Hanlen, Commonwealth Scientific Industrial Research Organization
Legal entity identifier (LEI) work is also addressing unstructured data, as Karla McKenna, head of standards at the Global Legal Entity Identifier Foundation, noted in June, saying entity legal form information – a data element in the LEI repository – remains in "unstructured form."
When addressing unstructured data, Hanlen counsels that firms should realize there are two different types. "Unstructured data sitting inside the enterprise – in the customer relationship-management system, in fields called ‘other' – is like a hole in the ground that's yet to become a goldmine," he says. External unstructured data from sources such as social media and market surveillance is already being tapped for its golden value, as Hanlen describes.
Data analytics can come into play for the former type of unstructured data, he says. "The task for analytics of unstructured data is not to build a brand new goldmine, but to extract elements of information from that unstructured data."
CSIRO and Data61 have worked on analyzing payments, documents predicting market outcomes and price signals based on the likelihood of future events. The challenge Hanlen finds in working with such unstructured data of a predictive rather than measuring nature is placing that data in a credible spectrum, which can be used to anticipate the future or a likely outcome.
Unstructured data may be a goldmine, but it appears to be one that industry experts are just beginning to figure out how to tap, for a variety of purposes.
Jesse Lund talks about real uses for DLT in the capital markets, lessons learned while rolling out IBM's blockchain platform, and what’s ahead for 2018, and into 2019.Subscribe to Weekly Wrap emails