But, for those of us used to thinking about data – really thinking about it – we’re breaking new barriers every day. Because we are thinking about data in new ways – different than anyone has really approached data before.
Storage and delivery? That’s an afterthought. ‘Data science’ sounds cool, and is necessary – but it’s not the solution for defining context, quality and meaning.
Sure – governance is important. But a network of data stewards aren’t going to fix any problems endemic to semantic differences across silos. Big Data is not going to solve your data quality needs. Really. It isn’t. Centralizing your security and entity masters – wait, why are you doing that at all? That’s so 2005.
More ETL! What do you need to transform, and why do you need to? Maybe you’re using the wrong source to start with.
Say ‘We need a Data Lake’ to me one more time. I dare you.
Foundational things are hard. And non-sexy. Which makes them harder. No one is winning any awards for putting in a sidewalk. But get it wrong, there will be consequences. And this is where we start. And where we need to start. If we’re ever going to deliver your shiny decision dashboards with multi-colored moving graphs and predictive indicators, the foundation needs to be done right.
There is a significant lack of talent that understands data, or can (or wants to) think about data, in a way that is needed today. And many times, those hiring don’t know what they are hiring for. Not out of any fault of their own – new ground is being broken. When the internet was new and companies were trying to find designers and developers, there was a similar lack of understanding of what was needed, and a lack of good identifiable talent to do the jobs.
And data is at a crossroads today in much the same vein. Everyone is told they need someone who ‘gets data.’ But they don’t really know what they need. And probably, in the back of their mind, they don’t really believe they need someone who ‘gets data’ but instead just need a new tech guy that can say ‘data river’ in an interview.
Data folks understand the business. We understand the technology. And we understand data is hard. But we understand that context (semantics) is king and understanding people is key. True data professionals can cross boundaries, then translate and relate to the varying needs, languages and priorities across those boundaries and silos. And we need to constantly keep educating others, in the face of misinformation or folks grasping for information from the less informed. We’re not a ‘data scientist’ (though we may have played on in the past). We may have come from operations (it’s a good bet). We may know how to throw down an SQL query (but don’t bet on that one).
Data lives and breathes, and is what drives the business – more so than the technology that is used to deliver much of that data. So shouldn’t we all be giving at least as much attention to the data, its lifecycle, and the people managing that data as we give to the color pallet, fonts and stylesheets being applied to the dashboard delivering that data?
But when we, as data thought leaders, talk about the foundations and plumbing needed, there is a 3-Monkey response. Just deliver the sexy stuff. That’s what is getting funded.. not the core things. But we need to be sure to keep fighting for the foundational work. Because we know ignoring it is not bliss.
