I recently attended a talk by Linguamatics CTO David Milward on Structured Queries for Unstructured Data, delivered to the Data Insights Cambridge Meetup group.
The data science community wants to know:
How can we deliver insights from big data?
What are the optimal approaches to ‘handle’ (store, capture) and analyze (query, structure, repurpose) big data?
The amount of data we can store and generate is many times what we could store or capture just 10 years ago. SQL Database technology is able to handle structured data well and has not changed significantly since the 1980s. It’s easier to deliver insights from structured data for basic queries than it is for unstructured data in free text sources.
Unstructured data is the new frontier for data science
What drew so many people to David’s talk is the promise of the ‘data insights’ that are locked away in unstructured data. The audience spanned various industries, from those dealing with astronomical data to financial data sources, to many people concerned with health and life science unstructured data. Many industries rely heavily on data to inform their day to day business decisions. For healthcare and life science, where Linguamatics is the text mining leader, transforming how we understand and improve upon population health and patient outcomes will primarily entail extracting data insights from unstructured data sources.