Data driven decision-making is imperative for companies, enabling them to derive new business value, improve operational efficiency, increase competitive advantage, and respond to competitive threats. ^[1] There are multiple challenges associated with the successful utilization of data, however, including the time needed to identify the most relevant datasets for an organization given the enormous increase in volume and variety of data sources. 

The research team at a quantitative investment firm in Europe wanted to continually push the envelope and generate new ideas for the firm’s portfolio managers. Team members knew they needed to access and analyze a wide variety of information for this to happen ‒ an onerous task for a small shop. They wanted to find a faster and more efficient way to determine what datasets could yield cutting-edge insights.