Pivot Tables and BeyondPatrick Carey

Daily Sales from GJCTransactions from Green Jersey Cycles from 2010 through 2013.

Products TableTable displaying a selection of sample products sold by GJC

Stores TableTable displaying information about 20 brick & mortar stores and the GJC website

Count of Product ID’sThe COUNT function of Product ID’s gives an erroneous result since the same Product ID multiple times. We can correct this issue using the DISTINCOUNT function available under the Excel Data Model

Using Distinct CountCount of Products ID’s Discrete Count of Product ID’s

THE EXCEL DATA MODEL

Pivot Tables and Beyond

The Excel Data ModelThe Excel Data Model is attached to the workbook file, providing database tools and more compact and efficient data storage

Data Modeldatabase

Data Model OverviewBenefits• Ability to Define Relationships

between Multiple Tables• Data Compression• Support for DAX • Interfaces with Dashboarding

Tools like Power View

Limitations• Built-in Tools Missing from Pivot

Table Menus• Inability to Group Fields• Supported only in Excel 2013

Adding an Excel Table to the Data ModelYou can add a table to the Data Model when you generate the Pivot Table, by clicking the Add this to the Data Model checkbox

Distinct Count of Product ID’sThe DISTINCOUNT function available under the Excel Data Model counts each unique occurrence of a Product ID in the Sales table; from this we know that 212,720 units were sold from 35 different GJC products over the past 4 years.

Adding a Second TableTo use information from a second table, it has to be added to the Data Model and a relation established between the two tables.

Creating a Table Relationship

VIEWING THE DATA MODEL WITH POWERPIVOT

Pivot Tables and Beyond

PowerPivot Features

• View, edit, sort and filter data in the PowerPivot grid

• Perform Calculations using DAX• Set up table relations with a

graphic interface• Set default display formats for

data columns

• Hide Columns and Tables• Create hierarchies of data

columns• Define Key Performance

Indicators (KPI’s)• Analyze Big Data containing

Millions of Records

PowerPivot Data View

Importing Database Tables into the Data ModelMultiple database tables can be imported into the Data Model. Power Pivot will retain any table relations already defined in the database.

Table Relationships within Diagram ViewDiagram is useful for viewing the complete structure of your data model, including all relationships, hierarchies, and KPI’s. Here Sales Date in the Sales table and Date in the Calendar table are linked

Setting Column Sort OrderSorting Months by Month Number Sorting Weekdays by Weekday Number

Units Sold by Year and MonthIt’s important to define the sort order for the Year and Month fields so they are sorted in the correct order.

PIVOT TABLE CALCULATIONS USING DAX

Pivot Tables and Beyond

DAX• Data Analysis Expressions• Calculations based on

Tables and Columns• Support for Lookup Tables

and Table Relations

• Optimized Memory Engine supports Rapid Calculations over Large Columns and Tables

PowerPivot CalculationsCalculated Columns• Calculation context is row-based• Formulas are applied to an

entire column• Appear as a new columns within

PowerPivot Data View

Calculated Fields• Calculation is based on the

PivotTable context• Called measures in PowerPivot

2010• Appear in the Calculation Area

in PowerPivot Data View

Calculating Revenue from Each SaleTo calculate the revenue from each sales use the Unit Price field round in the Products table using the RELATED function to access the field valueRevenue:= [Units Sold]*RELATED([Products[Unit Price])

Total Revenue by Month and YearCalculated Columns appear in the list of table columns alongside data fields and can be directly used in any Pivot Table combination we wish.

Calculating the Total Store DaysGJC is not open every day, so we create the StoreDays calculated field to count up the number days minus the number of holiday dates from the Holidays table.Store Days := COUNT([Calendar[Date]) – COUNT(Holidays[Date])

Calculating Average Daily RevenueThe average revenue collected day can be inserted as a calculated field using the DAX expression:Daily Revenue := SUM([Revenue])/[Store Days]

Daily Revenue from the GJC StoresOverall the store earns an average of about $7,600 per day for the selected products. Individual stores earn anywhere from $58 up to more than $440 per day.

KEY PERFORMANCE INDICATORS

Pivot Tables and Beyond

Defining a KPI against an Absolute StandardKPI’s provide a visual indicator of how a base field performs versus a defined standard. Here we set an absolute value for Daily Revenue with “normal” or ”acceptable” ranging from $80/day to $160/day

Viewing a Key Performance IndicatorHigh performance values are indicated by a green ball, low performance by a red ball, and values within the target area are highlighted with the yellow ball.

KPI’s can Lose their Meaning when the Data is FilteredAn absolute standard loses its meaning when the data values filtered. In this almost all stores appear to be underperforming when measured against an absolute standard that should apply only when all product categories are included.

Calculate the Number of Brick & Mortar storesWe want to compare each Brick & Mortar store to the average daily revenue from the Brick & Mortar stores. We can do this by using a calculated field that calculates the average revenue per store. We start by creating an expression to count the number of Brick & Mortar stores

Calculate the Daily Revenue from Brick & Mortar storesNext we calculate the Daily revenue from Brick & Mortar stores only. Note that here and in the Brick Count field we use the ALL() function to ensure that we always count over all [City State], [City], and [StoreID] fields regardless of the Pivot Table layout.

Calculating Average Revenue per Brick StoreThe Average Daily Revenue from the Brick Stores is calculated using the expression:Brick Revenue Average := [Brick Revenue]/[Brick Count]

Creating a KPI using a Calculated FieldWe now revise the Daily Revenue KPI so that it uses the Brick Revenue Average calculated field. Low values are cut off at 40% of the target, medium values at cut off at 80% of the target value.

Comparing Stores Under Different FiltersAll Brick & Mortar Stores Brick & Mortar Stores by Market

Calculating the Maximum Daily RevenueDAX supports a wide variety of queries and calculations. For example the above expression uses the SUMMARIZE function to return the maximum revenue generated on any particular day.

Viewing Maximum RevenueThe greatest one-day intake for the company was about $22,000 from all sources. The greatest one-day result for the website was a little more than $10,000; from the combined 20 Brick & Mortar stores the greatest one-day take was more than $14,000.

MANAGING YOUR FIELDS AND TABLES

Pivot Tables and Beyond

Defining a HierarchyHierachies are used to group fields that have an inherit ordering. For example the location hierarchy orders stores from Region State City

Viewing a Hierarchy

Hierarchies can be added to a Pivot Table, appearing as nested field. To drill down into the hierarchy, click the [+] box.

Hiding ColumnsYou can clean up the clutter of unwanted fields by hiding them from the user; showing only those fields which are directly involved in the data analysis. You can also hide entire tables, such as the Holidays table, that contain only lookup values.

Creating PerspectivesYou can reduce clutter in the Power Pivot view of the Data Model by creating a perspectives, specifying which tables and fields are visible to the Power Pivot user. However, modifying the perspective does not affect the table/field list in Excel.

ANALYZING YOUR DATA WITH POWER VIEW

Pivot Tables and Beyond

Sales ReportThis Power View report tracks sales for different products category by region with each report element dynamically linked to the others.

Clothing Sales ReportGJC has been selling an increasing percentage of cycling clothing for women over the past four years as this Power View report demonstrates.

Brick & Mortar Stores ReportThis Power View report examines the Brick & Mortar stores, providing contact information, map location, and the daily revenue.

Customer ReportThis Power View report shows the location of Green Jersey Cycling customers and the products they bought.

Contact Information

Patrick CareyCarey Associates8502 Miller RoadVerona, WI 53593(608) 832 – 6313patrick1@careys.com