Gain the knowledge and skills to build more sophisticated spreadsheets, perform What-If analyses, apply functions, manipulate PivotTables, and use the advanced features of Excel to make and present better business decisions. I think Excel is powerful with the last part because it keeps things relatively simple, and I do truly believe in Occam's Razor for most business problems that arise.This hands-on Excel data analysis course will expand your ability to analyze large amounts of data and professionally present your results. are all tools to get you there, but you have to know what to do with them, just as me having a hammer and a chisel doesn't make me an artist. What I'm learning thus far though is that the most important part of the job, at least for me since I'm in business analytics consulting, is understanding what data is needed, what the data you get means, and then building a model/story around it to explain what to do next. I was pretty worried, and am still semi-worried, about transitioning to analytics because I'm not a CS guy or have a very technical background. Maybe it's just a virtue of my background, but my move is to use Python/Alteryx to aggregate and clean my data, but the bulk of the analysis actually takes place in Excel still. that can automate a lot more than people give it credit for. Excel has a lot more functionality via array formulas (i.e.A lot of end-users don't understand Tableau even, forget about a Jupyter Notebook, and will prefer outputs in Excel/PPT. The GUI is easy, which makes it user-friendly to the people you're delivering your analysis to.Having said all that, I wanted to expand slightly on why I think Excel is slightly underrated: That being said, because the job revolves around aggregating and analyzing large datasets, I do recommend you learn, at a minimum, PowerBI, or ideally Python Pandas/Numpy to make your life easier. if you can't do basic lookups/pivots, you're going to have a very bad time) and that Excel is underrated as a tool. Although I'm still very new to analytics, I tend to agree with the people here who say that Excel is both table-stakes (i.e. The questions to ask aren’t always obvious or easy to formulate.įor context, I'm an ex-CPA who moved into business analytics because I got tired of just supplying numbers/closing out books every month and wanted to be more of a "problem solver". The important skill is to ask the right questions that can guide your search for good metrics to get to answers. Join datasets, filter them, group by some dimensions and then apply some aggregations and visualize things. I would say fundamentally you are probably going to be doing the same operations across the Excel, SQL, Pandas stack. Excel/SQL first and if you want to move into more programmatic type of stuff you can start learning Python and Pandas. If I was you I wouldn’t invest my time trying to pick it up, the ROI is really small. Most of the VBA written is terrible, because people who wrote it aren’t programmers and learned it on the fly so it’s weirdly written code, often without any documentation. You can take your Pivot Tables to a whole new level if you can write DAX measures.ĭepending on where you work, there might be a lot of legacy workbooks that might need tweaks or to be maintained so you might need to know VBA. In terms of steep learning curves to tackle, you can learn DAX and a bit of relational modeling first. VBA is probably the last thing you should learn in modern excel.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |