Data-as-a-Platform (DaaP) is a business model in which a company collects, stores, and manages a large volume of data then offers it to external partners and third-party systems. For example, a company might collect data about their audience’s purchasing habits over time, then sell that data to a partner company so they can use it to inform their business decisions. In this way, the idea of DaaP is unique because it positions data—rather than a piece of software or hardware—as a commodity.
Data-as-a-Platform is significant because it’s centered around collecting as much raw data as possible, not on the analysis thereof. For a DaaP model to be successful, the host company must collect and maintain a large volume of compelling data. Businesses that pay for access to this data can then use it to make decisions without needing to do the heavy lifting of collecting, storing, and managing the database themselves.
DaaP is intended to bring a deeper understanding of customer habits and historical trends to multiple businesses in the same market, which provides a basis for more widespread data-driven, customer-focused business decisions. However, business concerns around competition and privacy best practices have prevented DaaP from becoming a prominent player in new customer acquisition trends. In the early 2010s, Data-as-a-Platform was expected to take over as the next iteration of Big Data, but the rise of other technologies like cloud computing and machine learning in the last decade has made it easier for companies of all sizes to collect, manage, and analyze their own data. This has dramatically reduced viable use cases for DaaP strategies.