Introduction to Power BI — The Beginning of Data for many things Intelligence I.

Power BI is one of the many tools that is used in Business Intelligence. Remember what Business Intelligence is? It is an approach wherein you use software tools to make compelling insight out of data for Decision makers.

So what Power BI helps you do in this case is simple, consider your organization, a data-driven one, or let’s say your organization is just getting to use data to solve it’s many problems, one key thing that company use to drive growth is to monitor KPI — Key Performance Indicator. Remember what KPI is? These are the unique metrics that organizations track to monitor growth, it could be ratio of retention to customer acquisition, could be revenue per employee and many other metrics. But one thing stands out for KPI, this is that they are the life metrics organizations monitor to breath. You can refer back to the slide for details of things around Business Intelligence and KPI.

Power BI is one of the tools available for doing Business Intelligence and the end product of works with Power BI is to create a Business Intelligence Dashboard which managers and decision makers can look through in seconds and make informed Decision.

Where Data and Data Scientist come into play for this is;

· The Acquisition of Data

· Manipulation of Data

· Modelling the Data

· Creating compelling Visualizations from the Data

· Guiding Decision makers to understand the visualizations.

Power BI allows a Data Scientist to do this on the fly in a somewhat behind the scene process and make Decision makers happy. This short tutorial is to get you into the feel of how Power BI does this.

What you have to look out for is the process by which you use the tool and it’s features to achieve your dashboard. We will be looking basically at the two points i.e Acquisition and simple Visualisations of Data in this tutorial and in further tutorials we will conclude the other points.

1. Data Acquisition

In Real life, Data is usually gotten from a Database or downloaded as a file and because you might need to join multiple Data together, let’s just say we see our data coming from a Database with multiple Table. For our example we will first get a csv file into power BI

The Get Data features allows you to get Data from a lot of sources and data types into power BI

The circled portion is the feature that let’s you get data from many sources into Power BI. If you click the drop down and then More, you see a list of data sources that can be Power BI can read data from. You could scroll down to see more on the application.

Once you pick the source of your data then click on connect

In our case we are getting a CSV file and then we hit Connect

Takes you to the source of your data and you can access whichever table you want, in our case the International Folder contains our “tables”.

And after you connect with the data you want to load it in, then you see a view such as this:

Panel to view your table before you load it into your workspace

This panel is for you to view your data, understands it and relate with it before you load it into your work-space for visualisation.

Then you proceed to loading your data into the workspace. Some things come alive on your dashboard once you load the datasets which are.

a.

Fields that shows the Table — labelled as A and the columns in the table labelled as B.

b.

.The circled field below that is on your Dashboard which allows you to view the Tables that have in your Fields.

This concludes loading Data into Power BI.

2. A very basic Visualization

This Simple virtualisation forms the root of all dashboards you will creating with Power BI.

Couple of things to note: Consider a typical work-space termed Report in Power BI.

a. Reports Icon: This icon takes you to the ‘Workspace’ where you build the dashboards i.e Visualisations of the metrics and things you want to see from your data

b. Visualisations: Comes bundled with the Reports Icon, you are able to pick whichever visualisation type you want to make use of, this usually depends on the kind of questions you are willing to answer from your data

c. A list of check box next to the columns contained in the data: This allows you to check which columns you are making your visualisations with. Again this depends on the kind of questions you are willing to answer from your data .

Revenue by Zip Code. Take careful note of the ticked boxes in the fields.

This marks the creation of your first minimal dashboard.

Task: Let’s say I want to observe revenue for my products over two countries.

1. Load the multiple files in your folder through Power BI load by Folder

Use the Folder source to get multiple tables in a folder

2. Preview, then click combine and Edit

Combine and Edit can be seen when you click the drop down in the combine icon

Shows the preview

3. On the edit pane shown below — and because we want to only make our visualisation for 2 countries, Mexico and Germany, we will filter off the remaining countries

The Drop down circled allow you to be able to see distinct values of the column and then be able to filter it.

4. Once you click on the drop down, you will be given the option to load more if it’s only one of the distinct values you are seeing. And after loading more you are able to un-select the values you don’t want to see

5. After which you click OK, then Close and Apply at the left upper part of the image above — with this you only have data for Germany and Mexico in your Report/Workspace.

6. Visualising the task

This shows the revenue by product ID for each country and the sum total for the two countries

The above shows first, the total revenue for both country for each product ID, then shows a differentiation of what each country contributes to the total revenue observed. The above is an example of a Stacked Histogram . Couple of things to note

a. The kind of visualisation picked

b. The fields

c. Axis, Legend and Values: Axis is usually your x-axis while values is the sum of Revenue in our case. Legend is more of a differentiating value hence Country in our case.

Task: Replicate this for 3 and 4 Countries in the data.

PS: Data can be gotten from International Sales File from this GitHub repository