XLOOKUP Function

I personally don’t know why it took this long for Microsoft Excel team to create XLOOKUP function. The fact that VLOOKUP is considered to be one of Excel’s most widely used functions reflects a strong demand in string look up tabulations. Surely, a multitude of VLOOKUP‘s limitations can be overcome with patience, helper columns, INDEX/MATCH, CHOOSE, OFFSET and other constructs. Yet, why would we use any workarounds, when we would rather utilize a more powerful function with multitude of applications? Meet, much anticipated XLOOKUP function, which was officially released to Office 365 subscribers in early February of this year. It offers a really long list of additional benefits; in today’s tutorial we will review 11 scenarios that take full advantage of the following XLOOKUP features:

  • LEFT lookup
  • Horizontal lookup
  • Multi-cell/array retrieval
  • Match based on wildcard conditions
  • Combination of Vertical AND Horizontal lookups
  • Lookup based on multiple criteria
  • Lookup in reverse order
  • Lookup for maximum/minimum values
  • Built-in Error Handling
  • Exact match by default
  • Flexible approximate match

Continue reading

Google Dataset Search

Google has been dominating web search for nearly two decades and it’s acquisition of YouTube resulted in the second most popular search engine in the world. Yet, it seemingly lost the product search niche to Amazon. It’s not surprising that amidst growing interest in all things data, including public and open data, this tech giant would be keen on developing a search product geared towards making dataset search easier. What is surprising, is how long it took them to develop and release this product, which was officially introduced to general public on January 23rd, 2020 after spending more than 16 months in beta testing. You can embark on your own dataset search journey here.

Continue reading

Getting started with Microsoft Power BI using Google Merchandise store data.


Getting started with Microsoft Power BI using Google Merchandise store data

          While I’m as loyal to Excel as the next analyst, when it comes to data visualization and interactive dashboards, Tableau is my tool of choice. If I need to analyze large data sets, I prefer to get cozy with the data by writing SQL queries in whichever database environment such data might be stored. In the meantime, the world does not stand still, and Microsoft has been making substantial progress with a product offering they called Power BI . In fact, this tool offers data preparation, data discovery, dashboarding and custom visualization features starting with a free version for up to 1 GB of stored files and a modest $10 monthly plan for the beefed up PRO version. It’s definitely long overdue, but I finally got around to playing with both: Power BI desktop and cloud-based versions, all while using publicly available data from nonetheless, but Google’s merchandise store. , available through their demo Google Analytics account. Which other etailer can boast growing their Cyber Monday sales by 274% to $54K, while keeping their marketing advertising budget under $ 100?

Continue reading

How to pass an analytics job test – Part II – MS Excel.


How to pass an analytics job test - Part II - Microsoft Excel

          Even with the rise of use of R, Python, SAS and other more scientific analytical tools, Microsoft Excel remains the most popular data analysis tool. While we have gone over a solution for an analytics job test in SQL last month , you are much more likely to encounter a job test in Microsoft Excel for your next analytics opportunity. While I would personally argue that this particular test is actually better solved with SQL, the employer believes that the applicants instead need to apply their Excel skills to demonstrate their proficiency and acumen. As before, we should start by asking questions about the problem at hand and trying to get as much clarification as needed or state our assumptions. However, since spreadsheets are less forgiving from the presentation point of view than the databases, I would strongly recommend that we would also take a few minutes to format any workbooks provided by the prospective employer. Chances are they would recognize your level of professionalism by looking at clean and presentable file. Your stylistic preferences might be different, but as a minimum I would remove gridlines, add filters/format as tables larger datasets, freeze panes, and add at least one to two colors to the otherwise monochrome layout.

Continue reading