I love Excel. It’s a bedrock of my blog and largely my “claim to fame” as an authority. That said, early on I intended this not to just be an Excel blog, because I saw the benefits of cross-training and versatility for bigger-picture thinking.
If you’re looking to improve your data skills, I encourage you to take this same approach and not get too married to any one tool or vendor. Of course, you can’t become an expert in everything, and specializing in certain areas may make sense given your circumstances. But if every analytics tool you are using or learning comes from one vendor, that could be a problem.
Here’s why:
You’re not diversified
This one’s most apparent, but worth stating: by focusing on one software program, you are staking your future more firmly on the future of a specific vendor or community.
Sometimes, this works out fine: if you get into a program as an early adopter, you can ride the wave of demand to some handsome rewards.
Myself, I would prefer not to be entirely invested to any given tool or vendor. Maybe you’re different, if you feel very strongly in being an expert in a specific platform.
What I’m saying here is that this one may have to do more with personal preferences and calculated risks.
There are, however, more universal reasons not to focus on one platform.
You see things from one angle
We often think that dabbling in a broad range of concepts and tools is an inefficient way of learning, but that’s not always true. Research tells us that we learn new ideas by relating them to what we already know. These connections are often most insightful when they come from disparate areas.
Now, this doesn’t mean that you need to learn everything about data, ever. But it does suggest that you approach the field from different angles, and work to bridge the connections.
Many of us come into the data world from spreadsheets. Go learn other tools (And not just Power Query! We’ll get into that in a second.) and connect the dots: how do you do the equivalent of a PivotTable in R? A VLOOKUP() in SQL?
Once you can see how different tools approach the same problem, you able to tease out universal standards and methods of data analysis. This gives you range to learn even more methods.
This ability to triangulate data methods often gives you a better look into the field as a whole than if you learn just one particular tool — or, as we’ll dig into next, vendor solution.
Your vendor didn’t invent data analysis
Power Query and Power Pivot are game-changers for Excel and bust many of the myths about the tool’s limitations.
That said, while the technology of these tools may be new, the concepts are not. Left outer joins have been around for decades, along with the relational data model. These are topics that are probably best learned outside of the Microsoft platform and with a good old-fashioned SQL database.
I’ve heard it said that Power Query and Power Pivot were built so that end-users don’t need to learn SQL to do SQL-like things. This may be a good arrangement for Microsoft, but I’m not sure it’s good for users.
The problem is that users dig in on one platform such that they lose context in the field as a whole. Microsoft did not invent the data model, but I sometimes wonder if novice Power Pivot users think they did.
Solution: Buying into the stack
The most fertile data work often comes when combining multiple data tools, or blending the slices of the data analytics stack.
As of this time, no one vendor or software solution covers each stack the best. Microsoft has come a long way with the Power Platform. But even Microsoft admits it doesn’t do everything best, which is why it’s become so much more collaborative with open-source tools like R or Python.
I would suggest data analysts not get too hung up on being an expert in any one vendor’s platform, but instead having the context to navigate and blend tools. This stack will take some iterating, and it will take some crossing vendors and softwares. However, it will provide a diversified depth and breadth of knowledge that rigid specialization won’t.
What do you think? Should analysts focus on one vendor or no? What’s the right approach to diversify? Pros and cons? Let me know in the comments.
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