Bain research shows that company leaders in data strategy are deriving benefits from investments and capabilities. Paul Callahan, a principal with Bain's IT practice, shares how companies are improving their data strategy using technology and architecture by focusing on four key investment areas.
Read the transcript below.
PAUL CALLAHAN: Our work with clients and our research shows us that there are a number of companies that are leaders in data strategy. And they're deriving real benefits from their investments and their capabilities. In fact, they're much more likely to make better decisions and also three times as likely to have 10%-plus revenue growth year over year.
One of the ways in which leaders are improving their data strategy is through the use of technology in architecture. There's four primary areas where companies are investing. First, companies are moving beyond the traditional data warehouse. They're getting a lot of benefits from using things like data lakes—Hadoop, for example—to give them greater flexibility in the way that they use data on a daily basis.
They're also adopting NoSQL data stores, which give them greater flexibility for a wider variety of use cases. For example, graph databases are being used for much, much more sophisticated relationships between large data sets. Companies are also processing more data through stream-based technologies. Given the sheer volume and velocity of data in today's companies, it's essential to capture this data and understand emerging patterns either at the point of generation or the point of arrival.
Third, cloud-based services are providing companies with much greater flexibility and more affordable ways to improve their data landscape.
Finally, leaders are supporting data democratization by providing self-service tools to put data back into the hands of end business users. We know that technology alone is not the solution. Leaders are investing in technology, but also, in parallel, incrementally improving their capabilities in terms of their processes, data governance, and data architecture in order to derive the greatest benefit from those investments.