Lab - Prepare data in Power BI Desktop
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Before you start this lab (unless you are continuing from a previous lab), select Launch lab above.
You are automatically logged in to your lab environment as data-ai\student.
You can now begin your work on this lab.
Tip
To dock the lab environment so that it fills the window, select the PC icon at the top and then select Fit Window to Machine.
The estimated time to complete the lab is 45 minutes.
In this lab, you commence the development of a Power BI Desktop solution for the Adventure Works company. It involves connecting to source data, previewing the data, and using data preview techniques to understand the characteristics and quality of the source data.
In this lab, you learn how to:
Open Power BI Desktop
Set Power BI Desktop options
Connect to source data
Preview source data
Use data preview techniques to better understand the data
Lab story
This lab is one of many in a series of labs that was designed as a complete story from data preparation to publication as reports and dashboards. You can complete the labs in any order. However, if you intend to work through multiple labs, for the first 10 labs, we suggest you do them in the following order:
Prepare data in Power BI Desktop << You are here. This is the lab for the current module.
Note
Each lab starts with a PBIX file that has all of the previous lab work completed. If you should lose your work for any reason, you can open the PBIX file that includes the progress up to that point from the folder indicated at the beginning of the next lab.
Exercise 1: Prepare data
In this exercise you will create eight Power BI Desktop queries. Six queries will source data from SQL Server, and two from CSV files.
Task 1: Save the Power BI Desktop file
In this task, you will first save the Power BI Desktop file.
To open the Power BI Desktop, on the taskbar, select the Microsoft Power BI Desktop shortcut.
To close the getting started window, at the top-left of the window, select X.
To save the file, select the File ribbon tab to open the backstage view.
Select Save.
In the Save As window, navigate to the D:\DA100\MySolution folder.
In the File Name box, enter Sales Analysis.
Select Save.
Tip
You can also save the file by selecting the Save icon located at the top-left.
Task 2: Set Power BI Desktop options
In this task, you will set Power BI Desktop options.
In Power BI Desktop, select the File ribbon tab to open the backstage view.
At the left, select Options and Settings, and then select Options.
In the Options window, at the left, in the Current File group, select Data Load.
The Data Load settings for the current file allow setting options that determine default behaviors when modeling.
In the Relationships group, clear the two options that are selected.
While these two options can be helpful when developing a data model, they have been disabled to support the lab experience. When you create relationships in Lab 03A, you will learn why you are adding each one.
Select OK.
Save the Power BI Desktop file.
Task 3: Get data from SQL Server
In this task, you will create queries based on SQL Server tables.
On the Home ribbon tab, from inside the Data group, select SQL Server.
In the SQL Server Database window, in the Server box, enter localhost.
In the labs, you will connect to the SQL Server database by using localhost. This isn’t a recommended practice, however, when creating your own solutions. It’s because gateway data sources cannot resolve localhost.
Select OK.
Notice that the default authentication is to Use My Current Credentials.
Select Connect.
When prompted about encryption support, select OK.
In the Navigator window, at the left, expand the AdventureWorksDW2020 database.
The AdventureWorksDW2020 database is based on the AdventureWorksDW2017 sample database. It has been modified to support the learning objectives of the course labs.
Select but don’t check the DimEmployee table.
In the right pane, notice a preview of the table.
The preview allows you to determine the columns and a sample of rows.
To create queries, select the following six tables:
- DimEmployee
- DimEmployeeSalesTerritory
- DimProduct
- DimReseller
- DimSalesTerritory
- FactResellerSales
To apply transformations to the data of the selected tables, select Transform Data.
You won’t be transforming the data in this lab. The objectives of this lab are to explore and profile the data in the Power Query Editor window.
Task 4: Preview SQL Server queries
In this task, you will preview the data of the SQL Server queries. First, you will learn relevant information about the data. You will also use column quality, column distribution, and column profile tools to understand the data, and assess data quality.
In the Power Query Editor window, at the left, notice the Queries pane.
The Queries pane contains one query for each selected table.
Select the first query DimEmployee.
The DimEmployee table stores one row for each employee. A subset of the rows represent the salespeople, which will be relevant to the model you’ll develop.
At the bottom left, in the status bar, notice the table statistics - the table has 33 columns, and 296 rows.
In the data preview pane, scroll horizontally to review all columns.
Notice that the last five columns contain Table or Value links.
These five columns represent relationships to other tables in the database. They can be used to join tables together. You will join tables in Lab 03A.
To assess column quality, on the View ribbon tab, from inside the Data Preview group, select Column Quality.
Column quality allows you to easily determine the percentage of valid, error, or empty values.
For the Position column (sixth last column), notice that 94% of rows are empty (null).
To assess column distribution, on the View ribbon tab, from inside the Data Preview group, select Column Distribution.
Review the Position column again, and notice that there are four distinct values, and one unique value.
Review the column distribution for the EmployeeKey (first) column—there are 296 distinct values, and 296 unique values.
When the distinct and unique counts are the same, it means the column contains unique values. When modeling, it’s important that some tables contain unique columns. You can use these unique columns to create one-to-many relationships, which you will do in the Model Data in Power BI Desktop, Part 1 lab.
In the Queries pane, select the DimEmployeeSalesTerritory query.
The DimEmployeeSalesTerritory table stores one row for each employee and the sales territory regions they manage. The table supports relating many regions to a single employee. Some employees manage one, two, or possibly more regions. When you model this data, you’ll need to define a many-to-many relationship, which you’ll do in the Model Data in Power BI Desktop, Part 2 lab.
In the Queries pane, select the DimProduct query.
The DimProduct table contains one row per product sold by the company.
Horizontally scroll to reveal the last columns.
Notice the DimProductSubcategory column.
When you add transformations to this query in the Load Data in Power BI Desktop lab, you’ll use the DimProductSubcategory column to join tables.
In the Queries pane, select the DimReseller query.
The DimReseller table contains one row per reseller. Resellers sell, distribute, or add value to Adventure Works’ products.
To view column values, on the View ribbon tab, from inside the Data Preview group, select Column Profile.
Select the BusinessType column header.
Notice that a new pane opens beneath the data preview pane.
Review the column statistics and value distribution.
Notice the data quality issue: there are two labels for warehouse (Warehouse, and the misspelled Ware House).
Hover the cursor over the Ware House bar, and notice that there are five rows with this value.
You’ll apply a transformation to relabel these five rows in the Load Data in Power BI Desktop lab.
In the Queries pane, select the DimSalesTerritory query.
The DimSalesTerritory table contains one row per sales region, including Corporate HQ (headquarters). Regions are assigned to a country, and countries are assigned to groups. In the Model Data in Power BI Desktop, Part 1 lab, you’ll create a hierarchy to support analysis at region, country, or group level.
In the Queries pane, select the FactResellerSales query.
The FactResellerSales table contains one row per sales order line - a sales order contains one or more line items.
Review the column quality for the TotalProductCost column, and notice that 8% of the rows are empty.
Missing TotalProductCost column values is a data quality issue. To address the issue in the Load Data in Power BI Desktop lab, you'll apply transformations to fill in missing values by using the product standard cost, which is stored in the DimProduct table.
Task 5: Get data from a CSV file
In this task, you will create a query based on a CSV file.
To add a new query, in the Power Query Editor window, on the Home ribbon tab, from inside the New Query group, select the New Source down-arrow, and then select Text/CSV.
In the Open window, navigate to the D:\DA100\Resources folder, and select the ResellerSalesTargets.csv file.
Select Open.
In the ResellerSalesTargets.csv window, review the data preview.
Select OK.
In the Queries pane, notice the addition of the ResellerSalesTargets query.
The ResellerSalesTargets CSV file contains one row per salesperson, per year. Each row records 12 monthly sales targets (expressed in thousands). The business year for the Adventure Works company commences on July 1.
Notice that no columns contain empty values. When there isn’t a monthly sales target, a hyphen character is stored instead.
Review the icons in each column header, to the left of the column name.
The icons represent the column data type. 123 is whole number, and ABC is text.
You’ll apply many transformations to achieve a different shaped result consisting of only three columns: Date, EmployeeKey, and TargetAmount in the Load Data in Power BI Desktop lab.
Task 6: Get additional data from a CSV file
In this task, you will create an additional query based on a different CSV file.
Use the steps in the previous task to create a query based on the D:\DA100\Resources\ColorFormats.csv file.
The ColorFormats CSV file contains one row per product color. Each row records the HEX codes to format background and font colors. You’ll integrate this data with the DimProduct query data in the Load Data in Power BI Desktop lab.
Task 7: Finish up
In this task, you'll complete the lab.
On the View ribbon tab, from inside the Data Preview group, clear the three data preview options:
- Column quality
- Column distribution
- Column profile
To save the Power BI Desktop file, on the File backstage view, select Save.
When prompted to apply the queries, select Apply Later.
Applying the queries will load their data to the data model. You’re not ready to do that, as there are many transformations that must be applied first.
If you intend to start the next lab, you can opt to leave Power BI Desktop open.
Warning
If you leave the lab open, it will time out after one to four hours. Your work in the current module's lab will be lost, but each lab after the first one includes a PBIX file with the work from all previous labs completed so that you don't need to start over.
You’ll apply various transformations to the queries and then apply the queries to load them to the data model in the Load Data in Power BI Desktop lab.
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