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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
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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 • 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