Adventure Works: Power Bi

For this project, I visualized the sales and returns data from a bike shop called Adventure Works using Power BI. I visualized global data spanning time periods, goods, and customers using methods I learnt in the course.

I chose to utilize this project solely as a way to learn visualization and analysis techniques.

The Data:

I began by organizing the tables, connecting and structuring the data, and performing basic data quality assurance. Then, after learning about relational models, cardinality, and filter flow, I made my own data model.

Here, I am attaching the data model for better understanding of the available datasets.

Following to this, I used some of the interesting DAX functions to create new measures which will be useful for further analysis.

Some of my favorites' and very powerful DAX functions are,

CALCULATE() : it allows you to overrule existing report filters and “force” new filter context.

RELATED() : Returns related values in each row of a table based on relationships with other tables.

ALL(): Returns all rows in a table, or all values in a column, ignoring any filters that have been applied.

Iterator Functions: Iterator (or “X”) functions allow you to loop through the same expression on each row of a table, then apply some sort of aggregation to the results (SUM, MAX, etc.)

After Creating A new separate tables for created measures, finally comes the visualization part.

I created 4 dashboards and 1 Decomposition tree which are pretty much required depth knowledge of visualization skills. I am attaching screenshots of dashboards to share details and findings.

1)???Executive Dashboard – A high level summary of the entire data set.?

Key Insights:

• I started with executive level KPIs, which shows total revenue, profit orders and return rate of products. I also added three more KPI cards to give idea about how company manages to achieve monthly target compared to the previous month. I set monthly target 10% more than last month for revenue, orders and returns. Here we can see that only orders category fell short to achieve its monthly target. I tried to highlight this achievement using conditional formatting.
• I was able to include some drill through functionality after introducing the table with the top 10 products and the orders, revenue, and return rate linked to them. This indicates that you may examine more information about a single product by clicking on it to access a different dashboard (the Product Detail Dashboard).
• Introduction of the filter at top right corner allows user to filter through different years and continent. Here is the result of dashboard showing numbers for Year 2021 and North America continent.

2) Map – A visual to learn about using geospatial data & tooltips.

3) Product Details Dashboard: This dashboard is drill through Type, Which shows more details for particular products shown in the top 10 table of executive dashboard.

• One of the key things in this dashboard is the inclusion of gauge bars to show KPI numbers against the target for selected products.
• Also, there is adjusted price displayed using numeric parameters to compare weekly profit and adjusted profit.
• Lastly, I added different product metrics using field parameters to showcase the weekly trend of selected metric.

4) Customer Details: This dashboard displays customer level KPIs.

5 ) Decomposition Tree: I added decomposition tree using AI features available in Power Bi to show data (total orders) across different categories and subcategories.

Thank you, for reading the article.