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05/21/2014
1
“Power” Tools for IR Reporting
David Onder and Alison Joseph
AIR Annual Forum 2014
• 10,107 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
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2
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
5
Connecting to Data
Connecting to Data
• Wide variety of data sources, including:
– Access
– SQL Server
– Text files (csv)
– XML
– OLEDB
– Etc.
6
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3
Connecting to Data
• Connects to:
– Tables
– Queries
7
8
Connecting to Data
9
Connecting to Data
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4
10
Connecting to Data
11
Displaying Data –
Pivot Tables
Connecting to Data
12
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5
Connecting to Data
13
Displaying Data – Pivot Tables
14
Displaying Data – Pivot Tables
15
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6
Displaying Data – Pivot Tables
16
Sum
Count
Average
Max
Min
Product
Count Numbers
StdDev
StdDevp
Var
Varp
Displaying Data – Pivot Tables
17
18
Displaying Data –
Power Pivot
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7
Displaying Data – Power Pivot
• Set-up
19
• Installed with Excel 2013
• Downloadable add-in for Excel 2010
• Not available prior to Excel 2010
Displaying Data – Power Pivot
• The Power Pivot environment
20
Open Power Pivot
Displaying Data – Power Pivot
• The Power Pivot environment
21
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8
Displaying Data – Power Pivot
• Import data
22
Displaying Data – Power Pivot
• How the imported data look
23
Displaying Data – Power Pivot
• Bringing data into Excel
24
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9
Displaying Data – Power Pivot
• PivotTable vs. Power Pivot PivotTable
25
Displaying Data – Power Pivot
• DAX
– Data Analysis Expressions (DAX)
– Formula language for Power Pivot
– Used to create Calculated Columns and Calculated
Fields
26
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
27
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10
Displaying Data – Power Pivot
• Adding a calculated column
28
Displaying Data – Power Pivot
• Adding a calculated column
29
Displaying Data – Power Pivot
• Adding a calculated column
30
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11
Displaying Data – Power Pivot
• Adding a calculated column to pivot table
31
Evaluation Contexts
32
• Row context
• Filter context
• Row context
• Filter context
Evaluation Contexts
33
• The one row being evaluated
• Automatic for calculated columns
• Can be created in other ways as well (SUMX, AVERAGEX, etc.)
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Row Context
34
• Filter context
• The filters being applied by the pivot table
• Filters can be explicit or implicit
• Can add additional filters only with CALCULATE
Evaluation Contexts
35
• Row context
• The one row being evaluated
• Automatic for calculated columns
• Can be created in other ways as well (SUMX, AVERAGEX, etc.)
Filter Context
36
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13
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
37
Displaying Data – Power Pivot
• Adding a Calculated Field
38
Displaying Data – Power Pivot
• Adding a Calculated Field
39
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14
Displaying Data – Power Pivot
• Calculated Field in Power Pivot
40
41
Displaying Data –
Power Pivot
DAX
ALL, ALLEXCEPT, CALCULATE, DISTINCTCOUNT, DIVIDE, FILTER
Displaying Data – Power Pivot
• DISTINCTCOUNT
DISTINCTCOUNT( <column> )
– Counts unique values in column
42
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15
Displaying Data – Power Pivot
• Adding a Calculated Field
43
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
44
First-time Freshmen Distinct Students:=
CALCULATE(
[Distinct Students],
WorkshopData[Class level]=“Freshman”,
WorkshopData[Is new student this term]=“Yes”
)
45
Displaying Data – Power Pivot: DAX CALCULATE
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16
46
Displaying Data – Power Pivot: DAX CALCULATE
• 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
47
Displaying Data – Power Pivot: DAX ALL
All Distinct Enrolled Students:=
CALCULATE(
[Distinct Enrolled Students],
ALL( WorkshopData[Class level] )
)
48
Displaying Data – Power Pivot: DAX ALL
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17
49
Displaying Data – Power Pivot: DAX ALL
% of All Distinct Enrolled Students:=
DIVIDE([Distinct Enrolled Students],
[All Distinct Enrolled Students] )
50
Displaying Data – Power Pivot: DAX ALL
Displaying Data – Power Pivot
• DIVIDE
DIVIDE( <num>, <den>, [<alt>] )
– “Safe” divide
– Can specify alternate result for divide by zero
51
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18
Displaying Data – Power Pivot
52
Displaying Data – Power Pivot: DAX FILTER
• FILTER
FILTER( TableToFilter, FilterExpression )
– Returns a table filtered by FilterExpression
53
Above Average GPA Enrolled Undergraduates:=
CALCULATE(
[Distinct Enrolled Students],
FILTER(
WorkshopData,
WorkshopData[Institutional cumulative GPA] >
[Average GPA Enrolled Undergraduates]
)
)
54
Displaying Data – Power Pivot: DAX CALCULATE
05/21/2014
19
55
Displaying Data – Power Pivot: DAX FILTER
Displaying Data – Power Pivot: DAX FILTER
• ALLEXCEPT
ALLEXCEPT( <table>, <column>[, <column>…])
– Similar to ALL function, but excludes the column(s)
specified from the ALL
56
57
Displaying Data –
Power Map &
Power View
05/21/2014
20
Displaying Data – Power Map and Power View
• 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
58
Displaying Data – Power Map and Power View
59
Displaying Data – Power Map and Power View
60
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21
Displaying Data – Power Map and Power View
61
Displaying Data – Power Map and Power View
62
Displaying Data – Power Map and Power View
63
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22
Displaying Data – Power Map and Power View
64
Displaying Data – Power Map and Power View
65
Displaying Data – Power Map and Power View
66
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23
Displaying Data – Power Map and Power View
• Power View
– Dashboard builder
– Allows synchronized filtering
– Bring together tables, graphs, maps
67
Displaying Data – Power Map and Power View
68
Displaying Data – Power Map and Power View
69
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24
Displaying Data – Power Map and Power View
70
Displaying Data – Power Map and Power View
71
Displaying Data – Power Map and Power View
72
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25
Displaying Data – Power Map and Power View
73
Displaying Data – Power Map and Power View
74
Displaying Data – Power Map and Power View
75
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26
Displaying Data – Power Map and Power View
76
Displaying Data – Power Map and Power View
77
Displaying Data – Power Map and Power View
78
05/21/2014
27
79
Power Query –
Advanced
Power Query – Advanced
• 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
80
Power Query – Advanced
• Consolidate multiple
tables into one
81
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28
Power Query – Advanced
• In-line data
transformations
82
• Consolidate multiple
tables into one
Power Query – Advanced
• All transformation steps
are listed, and reversible
83
• In-line data
transformations
• Consolidate multiple
tables into one
Power Query – Advanced
• Access to sources of
data not readily
available to Power Pivot
84
• All transformation steps
are listed, and reversible
• In-line data
transformations
• Consolidate multiple
tables into one
05/21/2014
29
Power Query – Advanced
85
• Facebook pages and groups
Power Query – Advanced
• Drill down for
additional data
fields in facebook
records
• Availability of data
fields depends on
your personal
status with the
group/page, and
facebook data
fields completed
and available
86
Power Query – Advanced
87
• Employment data
05/21/2014
30
Power Query – Advanced
• Connect to online faculty database
– Import active users from Digital Measures
– Merge with local data
– Export updated data to Digital Measures
88
Power Query – Advanced
89
Power Query – Advanced
90
• Microsoft SQL Server and Access
05/21/2014
31
Power Query – Advanced
91
Power Query – Advanced
92
Power Query – Advanced
93
05/21/2014
32
Resources
94
• 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/)
Contact Information
Alison Joseph, Business and Technology Applications Analyst
ajoseph@wcu.edu
Office of Institutional Planning and Effectiveness
oipe.wcu.edu, (828) 227-7239
95
David Onder, Director of Assessment
dmonder@wcu.edu
With the help of Tim Metz, Elizabeth Snyder, Billy Hutchings, and Henson Sturgill

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2014 AIR "Power" Tools for IR Reporting

  • 1. 05/21/2014 1 “Power” Tools for IR Reporting David Onder and Alison Joseph AIR Annual Forum 2014 • 10,107 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
  • 2. 05/21/2014 2 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 5 Connecting to Data Connecting to Data • Wide variety of data sources, including: – Access – SQL Server – Text files (csv) – XML – OLEDB – Etc. 6
  • 3. 05/21/2014 3 Connecting to Data • Connects to: – Tables – Queries 7 8 Connecting to Data 9 Connecting to Data
  • 4. 05/21/2014 4 10 Connecting to Data 11 Displaying Data – Pivot Tables Connecting to Data 12
  • 5. 05/21/2014 5 Connecting to Data 13 Displaying Data – Pivot Tables 14 Displaying Data – Pivot Tables 15
  • 6. 05/21/2014 6 Displaying Data – Pivot Tables 16 Sum Count Average Max Min Product Count Numbers StdDev StdDevp Var Varp Displaying Data – Pivot Tables 17 18 Displaying Data – Power Pivot
  • 7. 05/21/2014 7 Displaying Data – Power Pivot • Set-up 19 • Installed with Excel 2013 • Downloadable add-in for Excel 2010 • Not available prior to Excel 2010 Displaying Data – Power Pivot • The Power Pivot environment 20 Open Power Pivot Displaying Data – Power Pivot • The Power Pivot environment 21
  • 8. 05/21/2014 8 Displaying Data – Power Pivot • Import data 22 Displaying Data – Power Pivot • How the imported data look 23 Displaying Data – Power Pivot • Bringing data into Excel 24
  • 9. 05/21/2014 9 Displaying Data – Power Pivot • PivotTable vs. Power Pivot PivotTable 25 Displaying Data – Power Pivot • DAX – Data Analysis Expressions (DAX) – Formula language for Power Pivot – Used to create Calculated Columns and Calculated Fields 26 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 27
  • 10. 05/21/2014 10 Displaying Data – Power Pivot • Adding a calculated column 28 Displaying Data – Power Pivot • Adding a calculated column 29 Displaying Data – Power Pivot • Adding a calculated column 30
  • 11. 05/21/2014 11 Displaying Data – Power Pivot • Adding a calculated column to pivot table 31 Evaluation Contexts 32 • Row context • Filter context • Row context • Filter context Evaluation Contexts 33 • The one row being evaluated • Automatic for calculated columns • Can be created in other ways as well (SUMX, AVERAGEX, etc.)
  • 12. 05/21/2014 12 Row Context 34 • Filter context • The filters being applied by the pivot table • Filters can be explicit or implicit • Can add additional filters only with CALCULATE Evaluation Contexts 35 • Row context • The one row being evaluated • Automatic for calculated columns • Can be created in other ways as well (SUMX, AVERAGEX, etc.) Filter Context 36
  • 13. 05/21/2014 13 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 37 Displaying Data – Power Pivot • Adding a Calculated Field 38 Displaying Data – Power Pivot • Adding a Calculated Field 39
  • 14. 05/21/2014 14 Displaying Data – Power Pivot • Calculated Field in Power Pivot 40 41 Displaying Data – Power Pivot DAX ALL, ALLEXCEPT, CALCULATE, DISTINCTCOUNT, DIVIDE, FILTER Displaying Data – Power Pivot • DISTINCTCOUNT DISTINCTCOUNT( <column> ) – Counts unique values in column 42
  • 15. 05/21/2014 15 Displaying Data – Power Pivot • Adding a Calculated Field 43 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 44 First-time Freshmen Distinct Students:= CALCULATE( [Distinct Students], WorkshopData[Class level]=“Freshman”, WorkshopData[Is new student this term]=“Yes” ) 45 Displaying Data – Power Pivot: DAX CALCULATE
  • 16. 05/21/2014 16 46 Displaying Data – Power Pivot: DAX CALCULATE • 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 47 Displaying Data – Power Pivot: DAX ALL All Distinct Enrolled Students:= CALCULATE( [Distinct Enrolled Students], ALL( WorkshopData[Class level] ) ) 48 Displaying Data – Power Pivot: DAX ALL
  • 17. 05/21/2014 17 49 Displaying Data – Power Pivot: DAX ALL % of All Distinct Enrolled Students:= DIVIDE([Distinct Enrolled Students], [All Distinct Enrolled Students] ) 50 Displaying Data – Power Pivot: DAX ALL Displaying Data – Power Pivot • DIVIDE DIVIDE( <num>, <den>, [<alt>] ) – “Safe” divide – Can specify alternate result for divide by zero 51
  • 18. 05/21/2014 18 Displaying Data – Power Pivot 52 Displaying Data – Power Pivot: DAX FILTER • FILTER FILTER( TableToFilter, FilterExpression ) – Returns a table filtered by FilterExpression 53 Above Average GPA Enrolled Undergraduates:= CALCULATE( [Distinct Enrolled Students], FILTER( WorkshopData, WorkshopData[Institutional cumulative GPA] > [Average GPA Enrolled Undergraduates] ) ) 54 Displaying Data – Power Pivot: DAX CALCULATE
  • 19. 05/21/2014 19 55 Displaying Data – Power Pivot: DAX FILTER Displaying Data – Power Pivot: DAX FILTER • ALLEXCEPT ALLEXCEPT( <table>, <column>[, <column>…]) – Similar to ALL function, but excludes the column(s) specified from the ALL 56 57 Displaying Data – Power Map & Power View
  • 20. 05/21/2014 20 Displaying Data – Power Map and Power View • 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 58 Displaying Data – Power Map and Power View 59 Displaying Data – Power Map and Power View 60
  • 21. 05/21/2014 21 Displaying Data – Power Map and Power View 61 Displaying Data – Power Map and Power View 62 Displaying Data – Power Map and Power View 63
  • 22. 05/21/2014 22 Displaying Data – Power Map and Power View 64 Displaying Data – Power Map and Power View 65 Displaying Data – Power Map and Power View 66
  • 23. 05/21/2014 23 Displaying Data – Power Map and Power View • Power View – Dashboard builder – Allows synchronized filtering – Bring together tables, graphs, maps 67 Displaying Data – Power Map and Power View 68 Displaying Data – Power Map and Power View 69
  • 24. 05/21/2014 24 Displaying Data – Power Map and Power View 70 Displaying Data – Power Map and Power View 71 Displaying Data – Power Map and Power View 72
  • 25. 05/21/2014 25 Displaying Data – Power Map and Power View 73 Displaying Data – Power Map and Power View 74 Displaying Data – Power Map and Power View 75
  • 26. 05/21/2014 26 Displaying Data – Power Map and Power View 76 Displaying Data – Power Map and Power View 77 Displaying Data – Power Map and Power View 78
  • 27. 05/21/2014 27 79 Power Query – Advanced Power Query – Advanced • 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 80 Power Query – Advanced • Consolidate multiple tables into one 81
  • 28. 05/21/2014 28 Power Query – Advanced • In-line data transformations 82 • Consolidate multiple tables into one Power Query – Advanced • All transformation steps are listed, and reversible 83 • In-line data transformations • Consolidate multiple tables into one Power Query – Advanced • Access to sources of data not readily available to Power Pivot 84 • All transformation steps are listed, and reversible • In-line data transformations • Consolidate multiple tables into one
  • 29. 05/21/2014 29 Power Query – Advanced 85 • Facebook pages and groups Power Query – Advanced • Drill down for additional data fields in facebook records • Availability of data fields depends on your personal status with the group/page, and facebook data fields completed and available 86 Power Query – Advanced 87 • Employment data
  • 30. 05/21/2014 30 Power Query – Advanced • Connect to online faculty database – Import active users from Digital Measures – Merge with local data – Export updated data to Digital Measures 88 Power Query – Advanced 89 Power Query – Advanced 90 • Microsoft SQL Server and Access
  • 31. 05/21/2014 31 Power Query – Advanced 91 Power Query – Advanced 92 Power Query – Advanced 93
  • 32. 05/21/2014 32 Resources 94 • 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/) Contact Information Alison Joseph, Business and Technology Applications Analyst ajoseph@wcu.edu Office of Institutional Planning and Effectiveness oipe.wcu.edu, (828) 227-7239 95 David Onder, Director of Assessment dmonder@wcu.edu With the help of Tim Metz, Elizabeth Snyder, Billy Hutchings, and Henson Sturgill