17-20 OCTOBER 2011
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17-20 OCTOBER 2011. DURBAN ICC. Killer Real-World PowerPivot Examples. Kevin Coetzee Online Systems Manager Dimension Data. Agenda. PowerPivot Overview Tips and Tricks for the Real World Working with PowerPivot for Business Real World Implementations HR Analysis
17-20 OCTOBER 2011
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Presentation Transcript
17-20 OCTOBER 2011 DURBAN ICC
Killer Real-World PowerPivot Examples Kevin Coetzee Online Systems Manager Dimension Data
Agenda • PowerPivot Overview • Tips and Tricks for the Real World • Working with PowerPivot for Business • Real World Implementations • HR Analysis • ATM Transactions with a little DAX • Payment Age Analysis with DAX and Related Tables • Some Tips and Tricks to take home
Business IntelligenceBI - Improving Business Insight “A broad category of applications and technologies for gathering, storing, analyzing, sharing and providing access to data to help enterprise users make better business decisions.” – Gartner
What is PowerPivotWith a few mouse clicks, a user can create and publish intuitive and interactive self-service analysis solutions
Demo : * HR Department* ATM Transactions* Aged Payment Analysis
Some Tips and TricksTip #1 • Use && and || in DAX • Instead of nested IF statements • Easier to read IF(Product[Color]=”Blue” && Product[Weight]>6, “Heavy and Blue”, “Everything Else”) IF(Product[Color]=”Blue”,”BlueProduct[Color]=”Red” || Product[Color]=”Yellow”, “Primary Color”, “Blend”)
Some Tips and TricksTip #2 : Less Columns / More Rows = Speed
Create a Date Table • STARTOFMONTH (Date_Column) • STARTOFQUARTER (Date_Column) • STARTOFYEAR (Date_Column [,YE_Date]) • ENDOFMONTH (Date_Column) • ENDOFQUARTER (Date_Column) • ENDOFYEAR (Date_Column [,YE_Date]) • PREVIOUSDAY (Date_Column) • PREVIOUSMONTH (Date_Column) • PREVIOUSQUARTER (Date_Column) • PREVIOUSYEAR (Date_Column [,YE_Date]) • NEXTDAY (Date_Column) • NEXTMONTH (Date_Column) • NEXTQUARTER (Date_Column) • NEXTYEAR (Date_Column [,YE_Date])
Rich Modeling Capabilities • Multiple relationships, hierarchies • Parent-child relationships • Key performance indicators, drillthrough, perspectives • Rich data types, BLOBs, images
Sophisticated Business Logic • Data Analysis Expressions (DAX), Excel formulas, MDX • Relational operators (Filter, Aggregate, GroupBy, Lookup) • Statistical, time intelligence (YTD, QTD) functions • Rank, TopN, VisualTotals, DistinctCount