Xyzology is a data literacy, data analytics, and data engineering blog with a particular focus helping teams at small and medium-sized organizations “do data right.” It also periodically features analytics of interest as part of its Xyzology Data Lab series.

I created Xyzology to address some all-too-common issues in data-driven workplaces:

Terms like data science, analytics, and data-driven are filled with buzz. It can be hard figuring out where to start and how to separate the actual substance in all that noise.

There is often a disconnect between the state of data technologies and the state of the industries using them. Just think of all the spreadsheet forests and paper forms you’ve had to deal with nonexistent or broken pipelines of information. Data has never been more accessible nor processes easier automate, but many organizations are terribly behind the curve.

Workplaces frequently warp data tools and resources to conform to outmoded processes. This creates dysfunctional work environments, damages user confidence in data platforms, and creates an all-around mess. Data teams expend so much precious energy “duct-taping” poorly-suited (or just poorly implemented) solutions together.

Data is a discipline full of self-taught professionals from all types of backgrounds. This is great because it enriches the field with invaluable expertise other than data work itself! It does, however, create situations where there are often some knowledge gaps. Maybe an analyst can work magic with SQL but is a complete novice at Javascript. That’s a problem as web-based applications are increasingly the platform of choice for data consumption. Perhaps an outstanding front-end developer can make JSON do ballet but gets disoriented navigating a data warehouse. That’s not great if the engineer is looking to optimize the data structures returned by their data storage APIs.

The leaders who steer organizations are often passionate champions of their vision but are data illiterate. You’ve probably encountered this during discussions of “metrics” or “creating a data-driven culture at this organization.” Their intentions are often noble, but their data illiteracy ultimately cripples their organization’s progress and productivity.

Now, I don’t have all the answers. I have, however, been around the figurative data block several times. I’m also keenly aware that my expertise comes from standing on the shoulder of some genuinely outstanding data peers, and I’m happy to share that knowledge in this blog.

I hope you use what you find here to do great things. I hope it empowers you to build fantastic tools or finally move that back-burner project forward. I hope you use it to advocate for positive change around data and get your organization on a path to data bliss…and I hope your boss gives you a huge raise as a result.

More than anything, however, I hope it helps you reclaim a substantial portion of the time all of us data professionals spend neck-deep in numbers, stewarding data all day.

Thanks for visiting and for joining me as this space develops!

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