Data Professionals in 2020
The technology landscape in 2020 and beyond is changing rapidly. Like all of my fellow data platform professionals, I know that I have to stay on top of the latest technologies. Unlike the past, Microsoft is fully embracing the open-source world. To stay relevant, my comfortable enclave of SQL Server, C#, and ASP.NET must expand to include tools I’ve avoided, up to this point.
As you may already know, I started out working with MySQL back around 2002. My teammates and I had several websites and processes running on our desktops. I can neither confirm nor deny the usage of “Do not unplug” sticky notes at this time. In 2003, when IT detected our “under the desk” servers, IT shut us down and forced us to move to corporate supported SQL Servers. And the rest is history. I’ve been working with SQL Server since then, including Reporting Services, Integration Services, and Analysis Services. As of this writing, I am studying for the SQL Server 2016 certification exams, so I am still working with SQL Server day in and day out.
Changes on the Horizon
In my current role, I support SQL Server users in offices all over the world. My day-to-day tasks usually occur on the development side of SQL Server. This includes performance tuning, optimizations, and report creation. I occasionally work on the infrastructure side of SQL Server, to keep that skill set sharp.
For the past couple of years, I was all in on SQL Server. I kept sharpening my skills, consuming all I could from all of the SQL Server celebrities. However, the dev teams were starting to introduce outside tools to our infrastructure. As the months passed, we noticed different teams were using things like Postgres, Node, Hadoop, MongoDB, CouchDB, and more. All of a sudden, we had Linux servers running alongside our Windows servers. The days of the full .NET stack were gone before my team noticed.
Hitting the Books Again
For 2020 I’ve decided to learn the following technologies for the following reasons:
- MongoDB – There were several open-source data platforms to choose from. I am going with MongoDB because I purchased a training class that leverages MongoDB on the back end.