Learning while Creating — Sometimes Part of a Whole is Enough.
Preamble.
I decided to acquire some skill in data analysis, beginning with Excel with an eye on other tools like SQL and BI tools. Excel does present itself as an interesting tool though and I am interested to see how far I can get in using it.
In the early days of picking an interest in DA (data analysis), I got my hands on some data, which I had absolutely no clue on how to proceed. As I continue this foray into Excel, some things are starting to make meaning to me.
The Data.
I picked up some ‘HR’ data and at first glance, I did not know what to do with it. It had some weird columns that were not totally filled, with some ‘termination’ dates into the future.
Cleaning and Transforming.
Having decided to focus on currently employed staff, I decided to remove the data of staff no longer in the employ of the company. I figured I could survive with 11.4% of the values removed. The next was to determine those who were employed by the company once they clocked 18. The data had those less than 18 working for the company so those were taken out of the worksheet as well. Going through these processes made me appreciate Power Query and the need to stick to one worktable (I created many, and the sheet was crowded to say the least).
Pivots and Analysis.
Every data has some insights that can be gained from it (even if the insight is ‘no insight here’). While there was no salary data to make it spicy, there was enough information to come up with some clues as to how the company has carried on with staffing in the past years.
The data spans from 2000 to 2020. In that time, the company’s staff steadily grew, and the data shows which discipline the company catered to more during employment. The data also shows the highest demographic count as well as the average age group of joining staff, and the highest average age group of current staff. In terms of location, I was able to determine the percentage of staff that worked onsite at the Headquarters, and those that worked remotely, as well as the staff strength in other states.
Conclusion: Working through the data.
I think I have come to respect Excel’s formulas. While I did consult some resources to get around some awkward parts, I enjoyed thinking through what I wanted to do and working up a formula to do it. I do admit that sometimes the formulas did not work on account of data formatting, but now I am wiser to that fact.
I look forward to acquiring more skills and working on more data. So far, the baby steps are encouraging.
