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T-SQL Tuesday #100: Looking forward 100 months

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I’ve only participated in 2 #tsql2sday events before this, so I am amazed that this is the 100th edition of Adam Machanic’s (t|b) uber-nerdy blog party.

Fittingly, Adam is the host for today’s shenanigans, and he has requested that we write about the landscape of the world of data professionals when #tsql2sday #200 comes around. Thanks for hosting Adam, and for getting this party started, way back in 2009!

It probably sounds a little bit dramatic, but I’ve been a little overwhelmed when I think about this topic. As Adam pointed out in the invitation, when this party started, the world was waiting for SQL Server 2008 R2. Personally, I was 18 months into my first job, writing SSRS reports, learning some very basic SSIS and compiling data extracts for ad-hoc queries. I had not yet ventured into the world of multidimensional cubes, I had only the faintest understanding of dimensional modelling, and I certainly had no idea that I would fall in love with data the way I have. I’m so happy with the way my career has progressed, and I love being part of the data community.

So here are my predictions for 2026:

Data professionals will be some of the most in-demand jobs in the world.

Contrary to many “thought-leaders” opinions that DBAs and other data professionals will be replaced by robots, I’d bet large portions of my (very-small) fortune on this one. The rate of data creation is not going to slow down, the number of requests for data from businesses is only going to increase, and data-driven decision making will become an even bigger factor in the way organisations, both small and large, operate. Yes, I hear you say, but they will be automated, and no longer require warm bodies. I say…

Organisations will still treat data quality as an afterthought.

Data scientists still spend between 60% and 70% of their time preparing data. Organisations would save themselves massive amounts of money by introducing robust and stringent data quality frameworks, but they won’t and data professionals will still spend their lives wrangling, munging and otherwise forcibly coercing data to look ok, instead of using their skills to add real business value. And speaking of things that would add business value…

Master Data will still be a pipe dream for all but the most mature environments.

Master data, the holy grail of data quality. So simple in theory, so rare in reality. Whenever I go to a new client, the first thing I ask is how their master data is managed. Those who don’t stare blankly, usually mumble something along the lines of “…we’d like to get there eventually.” I wish I could impress on customers how much better their data environments would be, and how much value they’d get from their data, with a comprehensive master data strategy, and a short-term investment in laying the groundwork for future success. Which leads nicely on to future lack of success…

Will Qlik disappear over the horizon?

Qlik (Qlikview and Qliksense) will have a tiny market share

QLIK Technologies is no longer trading on the Stock Exchange, so I don’t have any analysis to back this up, but my gut feeling is that the once market-leader will be, at best, a bit-part player in the BI space by 2026. I actually think this is already starting to happen, but there are enough large clients keeping Qlik afloat, for now. However, by 2026, I think that Microsoft will have continued on its current upward trajectory, and cannibalised a larger share of the market. As companies become more familiar with the cloud, and if MS continues to invest heavily in Power BI, I can’t actually see there being much competition at all, but for now I’m predicting that QLIK are going to be worst affected.

I don’t think that any of these are particularly brave predictions, but as Adam notes in his invitation, the rate of change is not as fast as we sometimes think it is. I could be totally wrong with everything I’ve predicted,

and maybe I will be, but I’m fairly certain that no matter what does change, and what doesn’t, the organisations who manage, use and curate their data best, will be the organisations that succeed in the future, and that is enough for me to be positive about a future as a data professional.

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