• #XDayofX

  • #100 days of learning Data Analytics as a newbie

Oyin What is it about? I can't wait to see it!

  • Created

    Jan '24

  • Last reply

    May '24
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    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

          Week 9-11

          I haven't been actively learning for 2 weeks now. Picking up where I left things this week🥹

            7 days later

            Solomon Hi Solomon!

            Thanks for following up on my updates

            It's nothing serious. I'm getting back on track gradually.

                Oyin Nice! I know it's not easy staying put especially when you are doing it all alone. I am impressed to see how far you have gone. However, it seems you have several other things you are pursuing and this is like a long term goal, right?

                • Oyin replied to this.

                    Week 12

                    I watched all the videos on SQL on Alex the Analyst YouTube channel. I am yet to practice anything on SQL, my laptop is faulty. It's up for repair, I will get it back next week.

                    7 days later

                    Week 13

                    My laptop is still up for repair, so I started reading the book 'Learning SQL' by Alan Beaulieu.

                    10 days later
                    5 days later
                    6 days later

                    Week 14

                    I started learning SQL from scratch with a course on Udemy. I'm about halfway done and I'm also going to be working on a project. I will share the project here when I'm done.