Data Model Assignment 1.pdf

1. Assignment: Analyzing Data with DAX Calculations in Power BI
Using the Bigbox report, complete the following:
1) In the DATA view, create the following calculated columns:
• In the Dim_Customer table, add a new column named "Customer
Priority" that equals "Priority" for customers who are under 50 years
old and have an annual income of greater than $100,000, and
"Standard" otherwise
• In the Dim_Product table, add a new column named "Price Point",
based on the following criteria
• If the product price is greater than $500, Price Point = "High"
• If the product price is between $100 and $500, Price Point =
"Mid-Range"
• If the product price is less than or equal to $100, Price Point =
"Low"
• In the Dim_Calendar table, add a new column named "Short Day"
to extract and capitalize the first three letters from the Day
Name column
• In the Dim_Product table, add a column named "SKU Category" to
extract the first two characters from the ProductSKU field
• BONUS: Modify the SKU Category function to
return any number of characters up to the first dash (Hint: You
may need to "search" long and hard for that dash...)
2) In the REPORT view, create the following measures (Use a matrix visual
to match the "spot check" values provided)
• Create a measure named "Product Models" to calculate the number
of unique product model names
• Spot check: You should see a total of 119 unique product
models

2. • Create a measure named "ALL Returns" to calculate the grand total
number of returns (not the number of items returned), regardless of
the filter context
• Spot check: You should see a total of 1,809 returns
• Create a measure to calculate "% of All Returns"
• Spot check: You should see a value of 61.64% for
the Accessories product category
• Create a measure named "Bike Returns" to calculate total returns for
bikes specifically
• Spot check: You should see a total of 427 bike returns
• Create a measure named "Total Cost", by multiplying order
quantities by product costs at the row-level
• Spot check: You should see a total cost of $14,456,986.32
• Once you've calculated Total Cost, create a new measure for "Total
Profit", defined as the total revenue minus the total cost
• Spot check: You should see a total profit of $10,457,580.86
• Create a measure to calculate Total Orders for the previous month
(named "Prev Month Orders")
• Spot check: Create a matrix with "Start of Month" on rows to
confirm accuracy
•
• Create a measure named "Order Target", calculated as a 10% lift
over the previous month
• Spot check: Create a matrix with "Start of Month" on rows to
confirm accuracy
• Total Returns for the previous month (named "Prev Month Returns")
• Spot check: Create a matrix with "Start of Month" on rows to
confirm accuracy
• 90-Day Rolling Profit (named "90-day Rolling Profit") (13:33 mark)

3. • Spot check: You should see a 90-day
rolling profit of $2,142,623.27
3) Save a separate backup copy of the .pbix file (i.e. "Bigbox
_Report_Backup")
HOMEWORK: Creating Table Relationships & Data Models in Power BI

4. Using your Adventure Works report file, complete the
following:
1) Navigate to the RELATIONSHIPS view, and perform the following
actions:
• Right-click to delete
each relationship between Fact_Sales, Dim_Customer and Dim_Cale
ndar (including both date fields)
• Use the Manage Relationships tool to delete all remaining
relationships between all tables
2) Recreate all table relationships (using any method you prefer), and
confirm the following:
• Cardinality is 1-to-Many for all relationships
• Filters are all One-Way (no two-way filters)
• Filter direction correctly flows "downstream" to data tables
• Data tables are not connected directly to one another
• Both data tables are connected to all valid (Dim) tables
• Product-related tables follow a snowflake schema
3) Return to the REPORT view, and complete the following:
• Edit (or insert) the matrix visual to show ReturnQuantity (values)
by CategoryName (rows) from the Dim_Products_Category table
• Which category saw the highest volume of returns? How
many?
• Replace CategoryName with Year from the Dim_Calendar table
• How many returns do you see in 2015 vs. 2016?
• Replace Year with FullName from the Dim_Customer table
• What do you see, and why?

5. • Update the matrix to show
both OrderQuantity and ReturnQuantity (values) by ProductKey (row
s) from the Dim_Products table
• What was the total OrderQuantity for Product #338?
4) Unhide the ProductKey field from the Fact_Returns tables (using either
the DATA or RELATIONSHIPS view):
• In the matrix,
replace ProductKey from Dim_Products with ProductKey from
the Fact_Returns table
• Why do we see the same repeating values for OrderQuantity?
• Edit the relationship between Fact_Returns and Dim_Products to
change the cross filter direction from Single to Both
• Why does the visual now show OrderQuantity values by
product, even though we are
using ProductKey from Fact_Returns?
• How many orders do we see now for Product #338? What's
going on here?
5) Complete the following :
• Change the cross filter direction
between Fact_Returns and Dim_Products back to single (One-Way)
• Hide the ProductKey field in the Fact_Returns table from report view
(and any other foreign keys, if necessary)
• Update the matrix to show ProductKey from the Dim_Products,
rather than Fact_Returns
• Recommendation: Save a separate backup copy of the .pbix file (i.e.
"AdventureWorks_Report_Backup")

6. Assignment: Visualizing Data with Power BI Reports
Using your Adventure Works report file, complete the
following:
1) Add a new report page named "Customer Detail", and complete the following
steps (Note: Screenshot provided for reference below):
• Add a matrix visual to show Total Orders and Total Revenue by customer
full name for the top 100 customers by revenue
• What happens when you try to pull in Total Returns as well? Why?
• Sort the matrix by Total Revenue (descending) to show the top revenue-
generating customers
• Spot check: You should Mr. Maurice Shan as the top customer,
with $12,407.96 in Total Revenue
• Add conditional formatting to show data bars on the Total Orders column
and a background color scale on the Total Revenue column, and customize
the style however you'd like
2) Add a Donut Chart to show Total Orders by Gender (on the Legend)
• Title the chart "Orders by Gender", and adjust formatting to match the
gauge charts on the Customer Detail tab (centered, gray background, light
gray font)
• Copy the chart and paste two more versions: one to visualize orders
by IncomeLevel, and a second to visualize orders
by Occupation (remember to update the chart titles!)
• Update the report interactions so that each donut chart (as well as the
matrix) filters the other two donuts, instead of highlighting (2:10 mark)
• Spot check: If you select "Mr. Maurice Shan" form the matrix visual,
you should see the charts filter to only show Gender = M, Income
Level = Average, and Occupation = Professional
• Hold CTRL to select all three donuts, and use the formatting tools to align
the top of each chart and distribute horizontally

7. 3) Add a Line & Clustered Column chart to show Total Orders (as columns)
and Total Revenue (as a line), with Start of Month on the shared X-axis
Update the chart title to "Orders & Revenue by Month", and format the chart style
however you choose
• Spot check: You should see that "Mr. Marco Lopez" drove the most
orders (3) in June 2017
• Select the matrix, and update the report interaction mode to filter the combo
chart (vs. highlighting)
• Spot check: You should see that "Mr. Marco Lopez" placed orders
in June 2016, August 2016, March 2017 and June 2017
4) Add a Treemap visual to show Total Orders (values) grouped by Current Age
Update the chart title to "Orders by Age", and format the chart style however you
choose
• Select the matrix, and update the report interaction mode to filter the
treemap (vs. highlighting)
• Spot check: Ages will change over time since they based on the
TODAY() function, but you should see the most orders for
age 50 and 49
5) Add a card to show FullName, and make the following updates:
• Turn off the Category Label, update the card title to "Top Customer", and
adjust formatting to match the donut charts
• Format with a light yellow background fill (to match the product cards on
the exec summary page)
• Add a Top N visual-level filter to show the #1 customer based on Total
Revenue
• Spot check: You should see "Mr Maurice Shan" when the view is
unfiltered, and "Mrs. Janet Munoz" when filtering on Female
customers only

8. • Copy and paste to create two new cards: one showing Total Orders, and the
other showing Total Revenue, and update card titles to "Customer Orders"
and "Customer Revenue", respectively
• Spot check: Among high income customers, you should see "Mrs.
Lisa Cai" as the top customer, with 7 orders and $11.33K in revenue
6) Add a text box that says "Executive Summary", and insert an arrow button next
to it
Return to the "Exec Summary" page, activate the bookmark tab, and add
a bookmark named "Exec Summary"
• Return to the "Customer Detail" page, and link the arrow button to the
bookmark you just created using the object "Action" properties
• Spot check: CTRL-click the arrow to confirm that the link works as
expected
7) Make any formatting tweaks that you see fit (alignment, chart styles, separation
lines, etc.), and save a (completed!) copy of the report
Report screenshot (for reference):