I and my team were given a task as stated below:
Choose a product in Nigeria or used by Nigerians and work on a product sales insight using Excel and Power BI.
You're to do the following:
Data Scraping
Data Cleaning
Data Visualization
........
In a bid to get a good dataset that meets these criteria, we went through the internet for days, but couldn't come up with a comprehensive dataset of Nigeria used products.
All we could lay our hands on that partly follows the requirements, was a dataset of telephone companies in Nigeria across the 36 states, as seen in link1.
Steps that Led to Our Sales insight:
<ul>
<li>Data Collection</li>
<li>Data Cleaning</li>
<li>Creating of 37 macros and 37 buttons. Each button is assigned to a macro that filters the name of each state, number of subscribers, and Network type.</li>
<li>Create a visual that represents the total number of Subscribers for each state.</li>
</ul>
Insight: From the visual (as shown in link1), if a company wants to run an ads to sell mobile subscription, targeting MTN might lead to less CPC due to the High number of users.
Adjustments: This dataset can further be resolved into Top 3 state with Highest Subscription per Network Type. This will help the company be more focussed on a state and network.

I and my team were given a task as stated below:

Choose a product in Nigeria or used by Nigerians and work on a product sales insight using Excel and Power BI.

You're to do the following:
Data Scraping
Data Cleaning
Data Visualization

........

In a bid to get a good dataset that meets these criteria, we went through the internet for days, but couldn't come up with a comprehensive dataset of Nigeria used products.

All we could lay our hands on that partly follows the requirements, was a dataset of telephone companies in Nigeria across the 36 states, as seen in link1.

Steps that Led to Our Sales insight:

- Data Collection
- Data Cleaning
- Creating of 37 macros and 37 buttons. Each button is assigned to a macro that filters the name of each state, number of subscribers, and Network type.
- Create a visual that represents the total number of Subscribers for each state.

Insight: From the visual (as shown in link1), if a company wants to run an ads to sell mobile subscription, targeting MTN might lead to less CPC due to the High number of users.

Adjustments: This dataset can further be resolved into Top 3 state with Highest Subscription per Network Type. This will help the company be more focussed on a state and network.

Data Analytics Group14 Portfolio Bootcamp