This article is part of The Bloor Group’s research program, Philosophy of Data, which has been underwritten by IRI, The CoSort Company.
The pen is mightier than the sword, and as such, words can be very powerful. They can enlighten, enrage, disrupt, inform – there is no end to the list of evocations words bring about. But taken out of context, the meaning can change completely. The same can be said about data.
While organizations struggle to find the “single version of the truth,” the fact is, data without context, or data in the wrong context, is not really useful at all. Rick Sherman, of Athena IT Solutions, said that many people he encounters have a misconception about what data actually is. He said that instead of thinking of data as something absolute, it’s more important to consider the context in which the data lives.
Each department within an organization, for example, may view the exact same enterprise data. Finance, sales, supply chain, marketing – they each approach that data from their own point of view. Sherman said this type of disconnect leads to frustration when business intelligence (BI) or data warehousing projects take longer than expected. “Generally, they’re sort of enterprise in scope. That means more context, more people, more viewpoints of the data,” he said.
It’s not so much the schemas and the modeling that take the most time, then, but rather understanding how to give all departments a view of the data that makes the most sense to them. In turn, that means letting go of pursuing a final definition of the truth.
“The Don Quixote never getting to the windmill, the truth, isn’t a bad thing,” said Sherman. “It’s that more and more truths or contexts are being applied today, which just means more and more expansive use of data.”
When data moves around, and the context in which it was generated is not maintained, meaning gets lost. In the case of business policies, practices such as undocumented hand coding, be it from ETL or application integration, can lead to what Sherman calls “data shadow systems.” It’s the age-old scenario where the left hand doesn’t know what the right hand is doing, and they both go on doing their own thing. The result? Inconsistency and inaccuracy.
“The business person who probably does understand policy and business processes doesn’t understand the technology and the data integration and the consistency of data and how to create that,” said Sherman. And by the same token, the technical team likely does not have the business context to model appropriately, leaving both sides frustrated. An organization can have all the latest tools and tips and technology at its fingertips, but without context and direction, initiatives can fall flat.
However, keeping track of data and its context is no easy task. Data has exploded, and with that explosion has come a wealth of opportunities and plenty of challenges. For decades, there has been the great divide between business and IT, where IT was responsible for managing, governing and delivering data, and business was in charge of reading what it had been given. Business decisions have certainly become more data-driven, and at the same time, business users want to turn that data into value without waiting for IT-generated reports.
Sherman said that in order for an enterprise to arrive at a data-driven culture, it must enable productivity and fast access to data, and it must embrace the fact that systems, businesses, people and data are complex. “We keep fooling ourselves,” he said. “We keep trying to run after solutions that are going to solve world hunger as opposed to the fact that data’s hard, data’s complex, and we need to accept that and work on that.”
Organizations may realize that data is an asset to be capitalized upon, but common pitfalls remain. Processes and cultures, especially when they’ve been in place for a number of years, are difficult to adjust. It is a human condition. Yet in the data management space, resistance to change can create unnecessary debates, arguments and outright refusal to accept new ideas or technologies, which in turn can cause expensive projects to fail.
One way to ensure success, said Sherman, is to allow for feedback during the development cycle. Understanding what processes people use, what data they look at and what they do with the data can be key to building out tools and applications that users are more likely to accept. With so much external or third party software available, the line of business no longer relies on IT for every report or dashboard. Yet it’s crucial that IT remains an enabler of business and provides data governance and context
At the end of the day, however, people are going to use whatever they can do get their job done, which is why context is so important. “If the data is in the right context,” said Sherman, “then what difference does it make what tool they use? They’ll arrive at the answer.”