Issue link: https://read.uberflip.com/i/1408661
5 This focus on bringing agility to data is new. As long as data was only transactional, we could lock it away in highly structured databases whose structure reflected the way it would be used for those transactions. Our tools were relational database systems such as Oracle or SQL Server, whose strengths are in transactional processing. We used the data to conduct the transactions themselves and to produce operational reports to support the transactions. To the extent that we paid attention to privacy, we enforced it by strictly limiting access to the data rather than searching for ways to make it available within the bounds of privacy guardrails. Instead of "privacy by design," we practiced a sort of "privacy by obscurity." Yes, there were attempts to free data for ad-hoc analysis with so-called business intelligence (BI) systems. But the tools have now advanced far beyond what BI systems were meant to do: We now have machine learning, a range of purpose-built databases to handle different types of data, algorithms for massively parallel processing, vast amounts of unstructured data like video and speech, IoT devices that deliver streams of sensor-derived data, and…well, just vast amounts of data. With these tools, we can free our data from its transactional and operational context. More importantly, we have realized that being data-driven is not just a technical challenge but also an organizational one. To be data-driven, an organization must think differently about how it makes business decisions and how it interacts with customers. It is a commitment to the value of data, a kind of organizational humility that says, "the data knows better than we do." How can we make our data available to be used in unexpected ways; that is, how can we use it flexibly to give us business agility? How can we apply it to bring rigor and creativity to business decision-making? How can we change business culture to take advantage of this new flexibility? And how can we put appropriate control guardrails around the data to safeguard its privacy while at the same time allowing it to be used flexibly and quickly? There are really two questions: 1 How can we bring agility to our data? 2 How can we use data to bring agility to our business? 5