Data Translator, giving data meaning. Ensuring analytics delivers business results. Podcast Speaker.
'Data isn't easy. It's incredibly complex.' Yes, I'm just stealing Dylan Anderson's newsletter headlines for my posts these days. And data is complex. Yet, as with everything we overcomplicate it massively. And we do so in a variety of ways. Processes We have been doing 'data' for decades, and technology helps us scale and do things faster than we used to. But this means we now attempt to do everything. If you previously had to wait a day for your query to run, you made damn well sure it was worth running. Tooling How many ways can you complete a simple data task? And in how many different tools? Yet the fundamentals are still the same. Now we have to join a load of disparate systems together. But you can get another tool which can do that... Job Roles Anyone know where to start with this one? Dylan makes the point that in order to deal with such complexity we develop silos to specialise in each area. This makes the problem worse as communication lines fail. Data teams end up siloed and further away from the areas in which they can have a business impact. And then we overcomplicate things as this gap widens. Some processes require complexity. Most don't. Where are you making your work more complicated than it needs to be? Discover more of my posts by following hashtag #datatranslator #data #analytics #technology P.S. check out Dylan's newsletter, it will get you thinking
Bridging the gap between data and strategy ✦ Head of Data Strategy @ Profusion ✦ Author of The Data Ecosystem newsletter ✦ R Programmer ✦ Policy Nerd
10moAha steal away my friend! Thanks for the mention and great builds on the idea. Honestly we don’t think it’s complex until we step outside our own domain and look at it from the perspective of another