It is both amazing and awesome to watch the capability and responsibility of data and reporting move into business roles which previously did not have that expectation as part of their job description.
Especially with the younger staff in businesses we notice. There’s appetite, capability, adoption and implementation all happening.
What does then arise is the tool vs tool conversations;
#excel vs #powerbi. Or #powerbi vs #googledatastudio vs #amazon #quicksights. Or #python vs the world. And #PowerQuery aka ‘Get & Transform’ vs a script that can pull data into #MongoDB.
What is important to remember, is that they are all just tools to get to an endpoint. And majority of the time the data and reporting “problem” comes with overloading tools. Data gymnastics happens when the tool is doing too much of the data work, which means;
**your work is not scalable
**the tools and reports are no longer performant
**there is a growing maintenance overhead
**there is no re-use which contributes chiefly to the previous three points
What skill should you learn? What is effective with almost every tool? What has been the backbone of data analytics for decades?
Structured Query Language baby
**It sits across so many database technologies
**The performance is there as the crunching is being done by the right tool, (the database / datalake) indexes can be added etc
**Your reporting tools aren’t generating horrible SQL
**You can cache it for further performance
**You can reuse it between multiple reporting tools
**You can do more with it than you think
So in my not so humble opinion the steps to scalable, reusable, performant reporting are;
1) Adopt an ETL tool (yes we have an awesome one)
2) Do some SQL Training (free short courses abound everywhere)
3) Build some skills that are universal and always in demand
4) Watch your reporting grow into a scalable, performant, maintainable and re-usable dream to work with
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