Information management comes together like the ’86 Mets

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As a kid watching the “Miracle Mets” win the 1986 World Series, I was enthralled with the way everything finally came together for that talented team — and I never thought I’d see the same thing taking shape in my industry decades later.

I’ve been in data and analytics long enough to remember when data and analytics were separate departments and they had no C-suite representation. Recently I’ve felt that every year we information management folks say, “Now we’re about to go mainstream.”

It started around 2012 with the big data revolution. In 2015, data science took us mainstream. Then came Internet-of-Things, then AI and ML, then data catalogs. If Gartner and Forrester both come out with research about a trend, you can be sure heads will turn.

But each time I got excited, there was always a kick. Is a new tool to locate and clean data really going to fundamentally improve information management businesses? Any more so than data visualization did circa 2005-2010? Was this really going to be the year that IT and business came together to change the industry?

Unfortunately, it never happened. When good technology came out of the enterprise, those creators were talking to each other more than mingling with the business users. Products look great drawn up on a whiteboard and analyzed and theorized ad infinitum. But until an organization implements it and users are achieving business ends, tech and business will remain separate, and enterprise’s will have to wait for its “miracle year.”

How Everyone Got Comfortable Using Data

But just because it hasn’t happened yet doesn’t mean it can’t happen next. I’m very excited about this current epoch. Not because we industry folks are changing—the data marketplace isn’t undergoing any sort of revolution—but because our partners are changing.

To put it bluntly, today’s business users are far more comfortable in their roles than their predecessors. They are awash in data and metrics; information that affects how they think and approach their jobs. This level of data acculturation is more important than knowing SQL or Hadoop precisely because it ensures that IT and business teams from executives to rank-and-file have a basis for conversing and collaborating.

Having observed this development gain steam very recently, my own team at Semarchy set out to solve for this concept. The idea is that, regardless of underlying bits and pieces, data must be consumable for non-tech lay users. This let to approach we call the intelligent data hub. Rather than treating master, reference and application data management as separate things from data governance or data quality/enrichment or workflows - what if you tackled all of them in parallel?

The data hub is what allows data scientists, operations managers, business strategists, and customer service reps to all have access to the same, right information to serve their vastly different ends. And the intelligent part is that layer of smart algorithms that processes more information than is humanly possible, without forgetting that all data is human data.

The Year Data Comes Together

So is this our year? It certainly wasn't for the Mets. Again. Is this the year information management breaks through and brings everyone to the table? I don’t know. But I do know that it’s starting to feel like all the right pieces are finally in the right place. It’s just the pieces are not necessarily what you think.

That’s why I’m reminded of that old Mets team. A great team doesn’t just have the best pitcher, the best catcher and the fastest runner, the same way a great industry doesn’t just generate a new buzzword every two years. Instead, it develops with ups and downs until finally the right mix of things comes together and the whole proves far greater than the sum of its parts.

In business as in sports, it’s always the team — never the individual — that makes the difference in success.

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