Excel Power Tools. David Onder and Alison Joseph. NCAIR 2015 Conference



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Transcription:

Excel Power Tools David Onder and Alison Joseph NCAIR 2015 Conference

10,382 students Master s Comprehensive Mountain location Residential and Distance 2

Why Pivot Tables Summarize large datasets Quickly add, remove, rearrange elements (Little to) No formula-writing Can be a basis for self-service data Can connect to a refreshable data source 3

Limitations of Pivot Tables Connected to only 1 table Formatting not maintained Calculated fields need to be created for each Pivot Table Can t count the way universities usually want to count 4

Displaying Data Pivot Tables 5

Connecting to Data 6

Connecting to Data 7

Displaying Data Pivot Tables 8

Displaying Data Pivot Tables 9

Displaying Data Pivot Tables Sum Count Average Max Min Product Count Numbers StdDev StdDevp Var Varp 10

Displaying Data Pivot Tables 11

Displaying Data Power Pivot 12

Displaying Data Power Pivot Set-up Installed with Excel 2013 Downloadable add-in for Excel 2010 Not available prior to Excel 2010 13

Displaying Data Power Pivot The Power Pivot environment Open Power Pivot 14

Displaying Data Power Pivot The Power Pivot environment 15

Displaying Data Power Pivot Import data 16

Displaying Data Power Pivot How the imported data look 17

Displaying Data Power Pivot Bringing data into Excel 18

Displaying Data Power Pivot PivotTable vs. Power Pivot PivotTable 19

Displaying Data Power Pivot DAX Data Analysis Expressions (DAX) Formula language for Power Pivot Used to create Calculated Columns and Calculated Fields 20

Displaying Data Power Pivot Calculated Columns Used to add an additional column to data table Can be a column added from a related table (like a VLOOKUP) or new data, derived from existing data (sum to combined SAT, length of name, substring of longer string, etc.) Column can be used in any area of the pivot 21

Displaying Data Power Pivot Adding a calculated column 22

Displaying Data Power Pivot Adding a calculated column 23

Displaying Data Power Pivot Adding a calculated column 24

Displaying Data Power Pivot Adding a calculated column to pivot table 25

Evaluation Contexts Row context Filter context 26

Evaluation Contexts Row context The one row being evaluated Automatic for calculated columns Can be created in other ways as well (SUMX, AVERAGEX, etc.) Filter context 27

Row Context 28

Evaluation Contexts Row context The one row being evaluated Automatic for calculated columns Can be created in other ways as well (SUMX, AVERAGEX, etc.) Filter context The filters being applied by the pivot table Filters can be explicit or implicit Can add additional filters only with CALCULATE 29

Filter Context 30

Displaying Data Power Pivot Calculated Fields Used to add a calculated element Aggregate function that applies to whole table, column, or range Something that needs to be recalculated Fields can only be used in the VALUES section 31

Displaying Data Power Pivot Adding a Calculated Field 32

Displaying Data Power Pivot Adding a Calculated Field 33

Displaying Data Power Pivot Calculated Field in Power Pivot 34

Displaying Data Power Pivot DAX ALL, ALLEXCEPT, CALCULATE, DISTINCTCOUNT, DIVIDE, FILTER 35

Displaying Data Power Pivot DISTINCTCOUNT DISTINCTCOUNT( <column> ) Counts unique values in column 36

Displaying Data Power Pivot Adding a Calculated Field 37

Displaying Data Power Pivot: DAX CALCULATE CALCULATE CALCULATE( expression, <filter1>, <filter2> ) Supercharged SUMIFS Allows filtering (IFs) on any aggregate function (imagine MAXIFS, MEDIANIFS, etc.) Operators for filters: =, <, >, <=, >=, <> Can also use in filter on same column 38

Displaying Data Power Pivot: DAX CALCULATE First-time Freshmen Distinct Students:= CALCULATE( [Distinct Students], WorkshopData[Class level]= Freshman, WorkshopData[Is new student this term]= Yes ) 39

Displaying Data Power Pivot: DAX CALCULATE 40

Displaying Data Power Pivot: DAX ALL ALL ALL( table_or_column, <column1>, <column2>, ) Returns all the rows in a table, or all the values in a column, removing any filters that might have been applied 41

Displaying Data Power Pivot: DAX ALL All Distinct Enrolled Students:= CALCULATE( [Distinct Enrolled Students], ALL( WorkshopData[Class level] ) ) 42

Displaying Data Power Pivot: DAX ALL 43

Displaying Data Power Pivot: DAX ALL % of All Distinct Enrolled Students:= DIVIDE([Distinct Enrolled Students], [All Distinct Enrolled Students] ) 44

Displaying Data Power Pivot DIVIDE DIVIDE( <num>, <den>, [<alt>] ) Safe divide Can specify alternate result for divide by zero 45

Displaying Data Power Pivot 46

Displaying Data Power Pivot: DAX FILTER FILTER FILTER( TableToFilter, FilterExpression ) Returns a table filtered by FilterExpression 47

Displaying Data Power Pivot: DAX CALCULATE Above Average GPA Enrolled Undergraduates:= CALCULATE( ) [Distinct Enrolled Students], FILTER( WorkshopData, WorkshopData[Institutional cumulative GPA] > [Average GPA Enrolled Undergraduates] ) 48

Displaying Data Power Pivot: DAX FILTER 49

Displaying Data Power Pivot: DAX FILTER ALLEXCEPT ALLEXCEPT( <table>, <column>[, <column> ]) Similar to ALL function, but excludes the column(s) specified from the ALL 50

51 Power Query

Power Query Retrieve data from a variety of external sources Pull in external data from the Internet Limit the data you bring into your model (filter on rows and columns) Keep you model to a reasonable size (< 1M records) to prevent processing problems Bring in only what you need 52

Power Query Consolidate multiple tables into one 53

Power Query Advanced Consolidate multiple tables into one In-line data transformations 54

Power Query Advanced Consolidate multiple tables into one In-line data transformations All transformation steps are listed, and reversible 55

Power Query Advanced Consolidate multiple tables into one In-line data transformations All transformation steps are listed, and reversible Access to sources of data not readily available to Power Pivot 56

Power Query Advanced SharePoint Lists 57

Power Query Advanced See all available lists Expand a particular list for fields 58

Power Query Advanced Even get Active Directory names 59

Power Query Advanced Connect to online faculty database Import active users from Digital Measures Merge with local data Export updated data to Digital Measures 60

Power Query Advanced 61

Power Query Advanced Microsoft SQL Server and Access An many other databases (e.g., Oracle, MySQL, PostgreSQL) 62

Power Query Advanced 63

Power Query Advanced 64

Power Query Advanced 65

Displaying Data Power View 66

Displaying Data Power View Power View Dashboard builder Allows synchronized filtering Bring together tables, graphs, maps 67

Displaying Data Power View 68

Displaying Data Power View 69

Displaying Data Power View 70

Displaying Data Power View 71

Displaying Data Power View 72

Displaying Data Power View 73

Displaying Data Power View 74

Displaying Data Power View 75

Displaying Data Power View 76

Displaying Data Power Map 77

Displaying Data Power Map Power Map Automated way to map geographic data Doesn t require geo-location information like longitude and latitude (just country, state, or county names) Can add elements to look at aggregate function on variables across physical space 78

Displaying Data Power Map 79

Displaying Data Power Map 80

Displaying Data Power Map 81

Displaying Data Power Map 82

Displaying Data Power Map 83

Displaying Data Power Map 84

Displaying Data Power Map 85

Displaying Data Power Map 86

Resources Rob Collie (http://powerpivotpro) DAX Formulas for PowerPivot, 2013 Bill Jelen (http://mrexcel.com) PowerPivot for the Data Analyst: Microsoft Excel 2010, 2010 Alberto Ferrari and Marco Russo Microsoft Excel 2013: Building Data Models with PowerPivot Chris Webb (http://cwebbbi.wordpress.com) Kasper de Jonge (http://www.powerpivotblog.nl) Purna Duggirala (http://www.chandoo.org/) 87

Contact Information David Onder, Director of Assessment dmonder@wcu.edu Alison Joseph, Business and Technology Applications Analyst ajoseph@wcu.edu Office of Institutional Planning and Effectiveness oipe.wcu.edu, (828) 227-7239 With the help of Tim Metz, Elizabeth Snyder, Billy Hutchings, and Henson Sturgill 88