Sheets!

I made a schema with too much data just in case I couldn’t find enough things to query. I had more than enough but I left it because I reasoned the purpose of the summary would be to quickly separate something more pertinent from the mass of data you might have about your employees.

First I divided the company into departments and summed the total amount of the salaries paid out to each as a whole. That worked great as a bar chart. Most of my information did and I wanted to mix it up for the assignment’s sake but I didn’t force anything into a pointless form. I later used a similar formula to include the profits made by the same departments and put it all a line graph for a comparison of who is making or losing the most money.

I made a chart that identifies how often people are absent by their ID number and it also specifies if they have children or not. The idea here being that kids are a common reason for needing to miss work.

There is a chart that lists each employee who actually has an account and what profits they are making from it. There is also a chart that represents how much profit is being made in every state where we have business.

For a second whole page chart, I found a very interesting and slightly confusing chart. If you tinker around and figure it out, it’s based on information of the start date of every employee who has a salary over $90,000. On the chart, you can scroll to a date and see the job title and salary of all people who started that day. You can also select a job title on the right and see a start date and salary for that title along with others that started that day. You can push the play button on the date line along the bottom and see a play through of the range of salaries since the company opened in chronological order until when the chart was created.

ALSO:

If I had this assignment to do over again, I would’ve included more numerical columns. It was a bigger challenge to make any compelling information out of two data strings. Since I won’t be able to handpick moldable data in the real world, I’ve learned that I really need to work on boolean queries. I’d also be interested in going deeper into a single employee and comparing their performance over time rather than several people in the same moment. I was trying something like that with the hire date vs. salary stats but not quite the way I intend to next time.

I can see this skill ranging from somewhat helpful to completely invaluable in every single endeavor. Obviously, corporations rely on charts and information like this constantly but even small scale instances like neighborhood committees or local fundraisers would benefit from a person with this skill transforming a sea of numbers into a bright, beautiful chart that can be absorbed. That saves time and brings glaring attention to potential oversights.

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