Thank you. I will definitely go back to it. Which resources are you using for learning?
#100 days of learning Data Analytics as a newbie
5 days later
Week 3
I completed the excel tutorial on w3school where i learnt functions and formulas. I speed read over 20 chapters of the Excel 2019 Bible. It has 48 chapters. I intend to complete it this month. Also, I have completed all my excel tutorials, I will be working on some excel project next.
7 days later
Week 4
I did more of reading this week. I speed read another 20 chapter of Excel 2019 Bible. I am left with about 5 chapters. I also downloaded some datasets on kaggle to work with. I am currently working on one.
8 days later
Week 5
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. - Edited
Week 6
Here's my first project - Here
It's about bike sales data. It's not perfect. I didn't achieve what I intended and made many mistakes too.
- The first sheet contains the raw data for the buyers.
- On the second sheet, I tried to clean the raw data.
- On the third sheet, I created two PivotTables showing the average income of people who purchased to identify which gender buys the most and customer commute to see which distance range buys the most.
- The fourth sheet also contains a PivotTable. I wanted to have all the PivotTables in one sheet, but it didn't work out. It kept changing the values in my previous tables. Here, I showed the age bracket of customers to see which age group buys the most. There's an invalid data on the chart. I think I got it while cleaning the age data.
- The fifth sheet shows the bike sales dashboard displaying the charts. I wanted to use the "Insert Slicer" feature to add more information to the charts, such as occupation, job title, region, and marital status of buyers, but it's not reflecting on the dashboard
If anyone gets to read this, I'd appreciate some feedback on my bike sales dashboard
If you were the bike store owner, could you use the dashboard I provided to make any business plans that would improve sales? If yes, which insights would you use to develop such plans? If no, what additional data do you think would be helpful for making better business decisions?
Nice work with the dashboard. I could see that majority of sales are coming from the middle aged customers and those with shorter commute distance. I would have loved to see what percentage of sales per occupation and per region.
Also, I would love to know why the comparison of those that bought and those that didn't buy is important. For me, the two information presented like that is hard for me brain to process meaning straight away.
Lastly, I noticed you used orange color as "Yes" in the first dashboard, then you used it to indicate "No" in the second and third dashboard. That can lead to some visual conflict if someone is not really careful.
To crown it all, how would love to know your own interpretation and insights as the analyst.
Solomon Thank you so much for your feedback. I really appreciate this. I would implement changes.
Regarding the comparison of buyers vs non-buyers, I just wanted to show overall buying trends.
For the colours it didn’t occur to me that I can change it. I just picked any chart I thought was easy to understand from the options given.
My interpretation of the data
I thought I would be told the problem they want to solve where I downloaded the data but I did not see any information
So, for me I think it's important to know the average income of both genders that bought bikes. This will help to understand the target market. The gap between the income of those that bought and didn't is little so, I think the store owner could stock different types of bikes so that the different income earners could pick what suits their income.
Also, the customer commute is to know which distance buy the most. From the chart those those with shorter commute distance buy the most. The store owner could consider opening stores in areas with longer commute distances. This could help increase sales.
The age bracket chart is to know the age range to target the most which is the middle age.
Although I know additional information like region, education and occupation would help make better decisions. I wanted to include them on the dashboard using the "insert slicer" feature but it's not reflecting on the dashboard maybe because I used Google sheet.
Week 7
I started with SQL and currently working on another project on Excel.
8 days later
Week 8
I didn't do much this week. I continued with SQL on w3school and read some articles on medium.
14 days later
- Edited
Week 9-11
I haven't been actively learning for 2 weeks now. Picking up where I left things this week