Microsoft's Power BI is a service for business analytics that offers interactive visualizations and business intelligence features with a user interface that is easy enough for end users to utilize to build their own reports and dashboards. It enables connections to several data sources, data transformation and cleaning, visualization creation, and sharing of findings with others.

Power BI offers an organized method for reviewing data and finding insights, making it a powerful tool for problem-solving. Clarifying the issue you're seeking to address is the first step in using Power BI to tackle it. This entails comprehending the enterprise issue, the queries you must address, and the insights you want. The next stage is to gather and prepare the data after the problem has been established.

In order to assist businesses find trends, patterns, and relationships in their data, Power BI offers a variety of data analysis capabilities. Businesses can spot possible issues and opportunities by using Power BI to analyze data and make wise decisions. Businesses may also develop visuals with Power BI, like as graphs, tables, and charts, to help them comprehend their data. Businesses can see trends and patterns by using Power BI to visualize data that may not be immediately apparent from raw data.

In this data digest, I will explore the following sub-topics highlighted below in a bid to improve your understanding of the Problem Solving Approaches in Power BI.

• Ingredients of Problem Solving
• Demo Case Studies
• How to improve critical thinking

Ingredients of Problem Solving

There are four (4) ingredients of problem solving which are listed below :

1. Knowledge
2. Tools
3. Common Sense
4. Problem Definition

Central to Power BI, what constitute knowledge is the fundamental of Power BI such as Power Query, building data model, data visualization and M language. The tools helps to apply the knowledge that are highlighted above in a bid to get the required result from a particular data. Common sense is the ability to distinguish between what is technically or analytically possible or not in this context. Problem definition is the process of identifying and clarifying a problem or issue that needs to be addressed. It involves understanding the problem's scope, impact, and causes, and identifying the desired outcome or solution.

Demo Case Studies

I will be walking you through different demo using the super store data set. I have created a calendar table in tandem with the super store data table and built a data model which is shown below.

On the calendar table, there are different hierarchy of date that are stored for the ease of analysis. This includes the full date itself, month, month number and year.

To start with, I will be working with the calendar table by leveraging a metrics visualization to format and critically align the months to a specific visualization usage.

• First, select the month to be on column from the calendar table and select the metric kind of visualization.

Note: Notice that PowerBI put the months in alphabetical order and not based on the normal calendar arrangement.

• To solve this problem - go back to the calendar table, select the month column to be sorted the select “select by column” option in the ribbon and sort by month number.

• This automatically changes the arrangement of the months in the metrics table.

• Next challenge, put the years on rows and the profit value with respect to each months and year.

Note: When presenting financial reports, it is always important to see the latest number first before the earlier numbers. This is important to that there is a good basis of comparison among the monthly profit over the years.

• If I am using an ordinary table with the months on the rows of the table, I can you the custom sort to fix this.

Note: When dealing with months on columns, to make December show first and January last, there is need to reverse the order, so January will have to change from 1 to 12, February will change from 2 to 11… and December will have to change from 12 to 1.

• To do this, I will create a new column with descending month by subtracting the month number from 13.

• Then, “select by column” option in the ribbon and sort by month number desc.

Alternatively, one can leverage the knowledge of number line to solve this same problem. The working concept is that the number on the left of any number is less than that specific number like (1 < 2, - 10 < -9, -2 < -1…).

• To implement this, one can makes the month numbers negative and then sort the month by the negative “month no”

• Then, there is no need to create columns but to sort the month column by the negative month number.

• This automatically orders the months in descending order.

Note: There are times when some firms do not use the normal calendar which is from January to December, but any other month range such as April - March. This will change the “year-month number” for the respective months. Simply put, April needs to be 1 and May will be 2 and then March will be 12.

• To do this, one needs to create a logic. This logic will be to (add 9) from January to March to give (10-12) and (subtract 3) from April to December to give (1-9). Select New Column called “FYMonth” and write the DAX code with the logic.

• Then, sort the columns by the FYMonth column

• The result will be a financial statement that is ordered from April to March

How to improve Critical Thinking in Power BI

• Finding the root cause of a problem and not the surface
• Delay in seeking for help
• Use pen and paper when problem solving
• Discuss and brainstorm with peers

Conclusion

Critical thinking is essential when creating and formatting visualizations in Power BI. It is important to consider the purpose of the visualization, the audience, the data being presented, and the best way to communicate the information effectively.

By using critical thinking, we can create visualizations that are clear, informative, and impactful. With the increasing importance of data-driven decision making, having the ability to create effective visualizations is becoming an increasingly valuable skill for professionals in many fields. By following the guidelines and best practices outlined in this data digest, we can create visualizations that help us to better understand and communicate complex data.

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