4 min read
The Analytics Engineer, made possible in part by TimeXtender!
In my previous blog in the Analytics Engineer blog series, I described what an Analytics Engineer is. In this new blog, I want to share how I discovered this new way of working thanks to TimeXtender. Thanks to the possibilities of a low-code solution like TimeXtender, a new way of working emerges that wasn't possible before. And this approach is particularly suitable and interesting for SME organizations.
The problem
A few years before I started at E-mergo, I worked as a Business Consultant. In this role I built Power BI reports with data straight from a CRM system, and I used data from Excel — a lot of Excel, to be honest. The amount of data and our ambitions ran into the limits of this setup, and we wanted to move up to the next level. So we looked at the tried-and-tested method of a Microsoft Data Warehouse with SSIS and Power BI on top. We got started with that. We found budget for a Data Engineer and went looking.
The search
That this failed turned out to be our good fortune in the end. What happened? Our search for a Data Engineer was difficult. We couldn't find anyone who was a good fit. We also had concerns about the single point of failure we were creating. In effect, we were caught between two stools: our ambitions were too big for our current setup, but our organization was too small for a full-fledged data team.
By chance we ended up in a TimeXtender demo at the time, where I realized: I can do this myself as a Business Consultant! Thanks to the accessible interface and the automation running in the background, I was suddenly able to build the data warehouse myself. That's why, instead of hiring one Data Engineer, we hired an extra Business Consultant. Now both of us held the conversations with the business, together we built the data warehouse in TimeXtender, and we both built the reports in Power BI. This saved us an enormous amount of time, while neither of us was a single point of failure.
- gathering the question from the business
- building the data structures
- and delivering the dashboards.
No intermediate steps are needed anymore in this process.
The Analytics Engineer as the solution
Later I came to realize that we had actually gotten started as Analytics Engineers back then.
As you can see in the figure above, besides the speed that TimeXtender's automation brought, we could also move faster with the business and deliver results. Of course you still need to carefully carry out all the steps from information analysis to building and testing the data warehouse, but there was no longer a handoff to other disciplines needed.
The result
Eventually we grew into a whole team of Analytics Engineers. That meant we could cover for each other during illness or vacation. As a result, we no longer had a single point of failure. TimeXtender helped us a lot with that too, through the automated documentation you get with it for free. Even more important is TimeXtender's interface; in it, data lineage is often clear in a single glance or a couple of clicks. And whenever it got very technical, or when we got stuck, we could always turn to E-mergo. So TimeXtender was really a key part of this new way of working! This is what made the Analytics Engineer approach possible for us.
Do you recognize the situation where you feel your current setup isn't enough to achieve your ambitions, but your organization is too small for a full data team? Then consider whether working with TimeXtender and Analytics Engineers is something for you.
Want to know more about this approach? Sign up for the live demo or get in touch with our colleagues. E-mergo is happy to think along with you.
Written by Stefan Timmerman
BI Consultant