Road to the MCSE

After my last MCP exam I got my MCSA in BI Reporting and my MCSE in Data Management and Analytics.  This was my 5th.

There are different advantages of these exams.  My first exam was the 70-768 about OLAP Cubes. I took that in July of 2017,  before the end of a long project that involved creating and managing lots of MOLAP cubes. I read 3 books for the exam not only to make sure that I pass but to make sure I also master the advanced level topics.  After I passed the exam I started to study other reporting tools knowing that I can move on from studying OLAP all the time.

The next one was the 70-779 Power BI exam in January 2018. It was harder to prepare for this one a bit because the exam ref. book was not published yet. I would say that about 6 months of working with Power BI is enough to pass the exam.

To understand different possible reporting achitectures on-premises or in the cloud, you should have a basic knowledge of Azure solutions so preparing for the 70-473 exam provided that for me. That exam also does not have an exam ref book but it had a practice test.

After these exams I thought that I need to improve my T-SQL skills so the next one became the 70-761. This is an example where unlike the Power BI exam I did not just prove that I have the skills by working with the technology. It was the other way this time, later I could use a lot of functions, solutions in my work from the practice test or the exam ref book.

My last exam so far is the 70-778 about Excel. I took it for two reasons, one was to get the certifications and the other was that I thought that every BI developer should take this exam becasue Excel is the most popular analytical tool. You can say that you don’t know Tableau or QlikView but you can’t say that you are not good at Excel.

I have kept on studying since the last exam because every book I read every video I watch takes me further on the road of becoming a data scientist.   What is a data scientist? My opinion is that it is more than a BI developer but still has to specialize in something. How many data scientist does it take to change a lightbulb? Two! The one is specialized in using a ladder, the other is specialized in turning things counter-clockwise.