Recently, I demonstrated a hypothetical data scenario that takes a fictional sports company called Velocity Sports and takes them through a data platform journey.
The aim of the demonstration is to show you how you can transform existing data sets or databases to gain intelligent insights that can be communicated across different internal and external stakeholders.
- Velocity Sports is a company that sells sporting goods. They have offices and retail stores within the United States.
- Currently, Velocity Sports stores their sales data on a on-premise Microsoft Access Database. However, they are looking for a cloud-based solution to securely store and manage their data.
- They store key sales data and want to be able to use this data to gain insights into how they are performing against their KPI’s.
- Finally, they want to be able to use their current sales data to predict future sales performance.
Proposed Data Platform
This scenario has three moving parts as shown in the basic diagram below:
As a basic overview, we’re going to move our database from Microsoft Access to Azure SQL. Then we’re going to connect our Azure SQL database to Power BI to draw some insights from our existing customer data through powerful Data Visualizations. Finally, I’ll export some data from Power BI that we want to gain future insights on that data using Azure Machine Learning.
This series of blog posts will have 3 parts:
- Moving our database from on-premise to the cloud.
- Gaining insights from our data using Power BI.
- Extract future insights using Azure Machine Learning.
I’m planning to put the files of this demonstration up on GitHub after I’ve done these blog posts. If you would like to see another hypothetical scenario using different technologies, let me know in the comments.