Taming Big Data: Integrating diverse public data sources for economic competitiveness analytics [Demonstration Proposal]
In an era where Big Data can greatly impact a broad population, many novel opportunities arise, chief among them the ability to integrate data from diverse sources and “wrangle” it to extract novel insights. Conceived as a tool that can help both expert and non-expert users better understand public data, MATTERS 1 was collaboratively developed by the Massachusetts High Tech Council, WPI and other institutions as an analytic platform offering dynamic modeling capabilities. MATTERS is an integrative data source on high fidelity cost and talent competitiveness metrics. Its goal is to extract, integrate and model rich economic, financial, educational and technological information from renowned heterogeneous web data sources ranging from The US Census Bureau, The Bureau of Labor Statistics to the Institute of Education Sciences, all known to be critical factors influencing economic competitiveness of states. This demonstration of MATTERS illustrates how we tackle challenges of data acquisition, cleaning, integration and wrangling into appropriate representations, visualization and story-telling with data in the context of state competitiveness in the high-tech sector.