Tutorial: Facebook analytics using Power BI Desktop

In this tutorial you learn how to import and visualize data from Facebook. During the tutorial you'll learn how to connect to a specific Facebook page (the Power BI page), apply data transformation steps, and create some visualizations.

Here are the steps you'll take:

Task 1: Connect to a Facebook Page
Task 2: Create visualizations using the Report view
- Step 1: Create a Treemap visualization
Task 3: Shape data in the Query view
- Step 1: Split the date-time column into two
- Step 2: Add an aggregate value from a related table
Task 4: Create additional visualizations using the Report view
- Step 1: Load the query to your report
- Step 2: Create a Line chart and a Bar chart

Task 1: Connect to a Facebook page

In this task you import data from the Microsoft Power BI Facebooksite (here's the URL: https://www.facebook.com/microsoftbi ).

Anyone can connect to that page, and follow these steps - no special credentials (other than your own Facebook account, which you use in this step) are required.

In the Getting Started dialog or in the Home ribbon tab, select Get Data.
The Get Data dialog appears, letting you select from all sorts of data sources. Select Facebook from the Other group.

When you select Connect, a dialog appears to alert you to the risks of using a third-party service.
When you select Continue, the Facebook dialog box appears where you can paste the page name (microsoftbi) into the Username text box. Select Posts from the Connection drop down.
Click OK.
When prompted for credentials, sign in using your Facebook account and allow Power BI access through your account.

After establishing a connection to the page, you will see the data being loaded in the model.

From there, Query Editor displays the data. Query Editor is part of Power BI Desktop, but loads in a separate window, and is where you perform all your transformations on your data connections.

When your data is how you want it, you can load it into Power BI Desktop. Select Load & Close from the Home ribbon.

You'll see a dialog that displays the progress of loading the data into the Power BI Desktop data model.

Once loaded, you’ll be taken to the Report view where the columns from the table are listed in the Field list on the right.

Task 2: Create visualizations using the Report view

Now that you have landed the data from the page, you can quickly and easily gain insights about your data, using visualizations.

Step 1: Create a Treemap visualization

Creating a visualization is easy, we just drag a field from the Field list and drop it on the Report canvas.

Drag the type field onto the Report canvas. Power BI Desktop creates a new visualization in the Report canvas. Next, drag type from Fields (the same field you just dragged onto the Report canvas) onto the Value area to create a Bar visualization.

We can easily change the type of visualization by selecting a different icon from the Visualization pane. Let's change the type to a Treemap by selecting its icon from Visualizations, as shown in the following image.

Next, let's add a legend, then change the color of a data point. Select the Format icon in the Visualizations pane; the Format icon looks like a paintbrush.

When you select the down arrow next to Legend, the section expands to show how to customize the legend for the selected visualization. In this case, we made the following selections:

moved the Legend slider to On so a legend would appear
selected Right from the Legend Position drop-down
moved the Title slider to On as well, so a title for the legend will appear
typed in type for the title of the legend

In the following image, those settings are already made and reflected in the visualization.

Next, let's change the color of one of the data points. The link data point should be blue, so it's closer to the common color for hyperlinks.

Select the arrow next to Data Colors to expand that section. The data points are shown, with selection arrows beside each color that allows us to select a different color for each data point.

When you click on the color box down arrow beside any data point, a color selection dialog appears, letting you choose your color. In this case, we'll choose light blue.

That's better. In the following image, you can see how the color is applied to the data point in the visualization, and that the legend is also automatically updated, as is its color in the Data Colors section.

Task 3: Shape data in the table

Now that you have imported the table selected and you start to visualize it, you may notice you need to perform various data shaping and cleansing steps in order to get the most out of your data.

Step 1: Split the date-time column into two

In this step, you will split the created_time column to get both the date and time values. Whenever you're in Power BI Desktop and you want to modify an existing query, you need to launch Query Editor. To do that, select Edit Queries from the Home tab.

In the Query Editor grid, scroll to the right until you find the created_time column
Right-click a column header in the Query Preview grid, and click Split Column > By Delimiter to split the columns. Chose Custom in the delimiter drop down and enter “T” Note that this operation is also available in the Home ribbon tab, in the Manage Columns group.
Rename the created columns to created_date and created_time respectively.
Select the new column, created_time, **** and in the Query view ribbon, navigate to the Add Column tab and select Time>Hour under the From Date & Time group. This will add a new column that is only the hour component of the time.
Change the type of the new Hour column to Whole Number, by navigating to the Home tab and selecting the Data Type drop down or by right-clicking the column and selecting Transform>Whole Number.

Step 2: Add an aggregate value from a related table

In this step, you add the count of shares from the nested value so that you can use it in the visualizations.

Continue scrolling to the right until you see the shares column. The nested value indicates that we need to do another transform in order to get the actual values.
In the top right of the column header, select the icon to open the Expand/Aggregate builder. Select count and hit OK. This will add the count of the shares for each row in our table.

After the data loads, rename the column to shares by double clicking on the column name, right clicking the column or in the Query view ribbon, select Rename under the Transform tab and Any Column group.
Finally, change the type of the new shares column to Whole Number. With the column selected, the type can be changed by right-clicking the column and selecting Transform>Whole Number or **** by navigating to the Home tab and selecting the Data Type drop down or.

Query steps created

As you perform transformations in the Query view, query steps are created and listed in the Query Settings pane, in the APPLIED STEPS list. Each query step has a corresponding Query formula, also known as the "M" language.

Task	Query step	Formula
Connect to a Facebook source	Source	Facebook.Graph ("https://graph.facebook.com/microsoftbi/posts")
Split Columns to get the values you need	Split Column by Delimiter	Table.SplitColumn (Source,"created_time",Splitter.SplitTextByDelimiter("T"),{"created_time.1", "created_time.2"})
Change Type of the new columns (automatic step)	Changed Type	Table.TransformColumnTypes (#"Split Column by Delimiter",{{"created_time.1", type date}, {"created_time.2", type time}})
Rename a column****	Renamed Columns	Table.RenameColumns (#"Changed Type",{{"created_time.1", "created_date"}, {"created_time.2", "created_time"}})
Insert a column****	Inserted Hour	Table.AddColumn (#"Renamed Columns", "Hour", each Time.Hour([created_time]), type number)
Change Type	Changed Type1	Table.TransformColumnTypes (#"Inserted Hour",{{"Hour", type text}})
Expand values in a nested table****	Expand shares	Table.ExpandRecordColumn (#"Changed Type1", "shares", {"count"}, {"shares.count"})
Rename the column****	Renamed Columns1	Table.RenameColumns (#" Expand shares",{{"shares.count", "shares"}})
Change Type	Changed Type2	Table.TransformColumnTypes (#"Renamed Columns1",{{"shares", Int64.Type}})

Task 4: Create additional visualizations using the Report view

Now that we have converted the data into the shape that we need for the rest of our analysis, we can load the resulting table into our Report and create additional visualizations.

Step 1: Load the query to your report

In order to load the query results to the report, we need to select Load & Close from Query Editor. This will load our changes into Power BI Desktop, and close Query Editor.

In Power BI Desktop, we need to make sure we're in Report view. Select the top icon from the left bar in Power BI Desktop.

Step 2: Create a Line chart and a Bar chart

In order to create a visualization, we can drag fields from the Field list and drop them in the Report canvas.

Drag the shares field onto the Report canvas, which creates a bar chart. Then drag created_date onto the chart, and Power BI Desktop changes the visualization to a Line Chart.
Next, drag the shares field and drop it in the Report canvas. Now drag the Hour field into the Axis section under the Field List.
We can easily change the type of visualization by clicking on a different icon in the Visualization pane. The arrow in the image below points to the Bar Chart icon.
Change the visualization type to Bar Chart.
The Bar Chart is created, but the axis isn't what we want - we want it sorted in the other direction (from high to low). Select the down arrow next to Y-Axis to expand that section. We need to change the type of axis from Continuous to Categorical, so it'll sort how we want it (the image below shows the axis before we make the selection - check out the subsequent image for how we want it to look).

That's better. And now we have three visualizations on this page, which we can size as we want to fill up the report page

As you can see, it's easy to customize visualizations in your report, so you can present the data in the way that you want. Power BI Desktop provides a seamless end-to-end experience from getting data from a wide range of data sources and shaping it to meet your analysis needs to visualizing this data in rich and interactive ways. Once your report is ready, you can upload it to Power BI and create dashboards based on it, which you can share with other Power BI users.

You can download the end result of this tutorial here