The Analyst's Perspective: Advanced BI with PowerPivot DAX, SharePoint Dashboards, and SQL Data Mining

Transcription

1 The Analyst's Perspective: Advanced BI with PowerPivot DAX, SharePoint Dashboards, and SQL Data Mining Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd 1 1

2 Objectives Introduce more advanced BI analytics from Microsoft Discuss using SharePoint 2010 as a BI Dashboard environment This seminar is based on a number of sources including a few dozen of Microsoft-owned presentations, used with permission. Thank you to Chris Dial, Tara Seppa, Aydin Gencler, Ivan Kosyakov, Bryan Bredehoeft, Marin Bezic, and Donald Farmer with his entire team for all the support. 2 The information herein is for informational purposes only and represents the opinions and views of Project Botticelli and/or Rafal Lukawiecki. The material presented is not certain and may vary based on several factors. Microsoft makes no warranties, express, implied or statutory, as to the information in this presentation. Portions 2010 Project Botticelli Ltd & entire material 2010 Microsoft Corp. Some slides contain quotations from copyrighted materials by other authors, as individually attributed or as already covered by Microsoft Copyright ownerships. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Project Botticelli Ltd as of the date of this presentation. Because Project Botticelli & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee the accuracy of any information provided after the date of this presentation. Project Botticelli makes no warranties, express, implied or statutory, as to the information in this presentation. E&OE. 2

3 3 PowerPivot DAX

4 Data Analysis Expressions (DAX) Simple Excel-style formulas Define new fields in the PivotTable field list Enable Excel users to perform powerful data analysis using the skills they already have Has elements of MDX but does not replace MDX 4 4

5 Data Analysis Expressions (DAX) No notion of addressing individual cells or ranges DAX functions refer to columns in the data Sample DAX expression Means: = [First Name] & & [Last Name] String concatenation just like Excel =SUM(Sales[Amount]) SUM function takes a column name instead of a range of cells =RELATED (Product[Cost]) new RELATED function follows relationship between tables 5 5

6 DAX Aggregation Functions DAX implements aggregation functions from Excel including SUM, AVERAGE, MIN, MAX, COUNT, but instead of taking multiple arguments (a list of ranges,) they take a reference to a column DAX also adds some new aggregation functions which aggregate any expression over the rows of a table SUMX AVERAGEX COUNTAX MINX MAXX (Table, Expression) (Table, Expression) (Table, Expression) (Table, Expression) (Table, Expression) 6 6 6

7 More than 80 Excel Functions in DAX 7 Date and Time Information Math and Trig Statistical Text DATE ISBLANK ABS AVERAGE CONCATENATE DATEVALUE ISERROR CEILING, ISO.CEILING AVERAGEA EXACT DAY ISLOGICAL EXP COUNT FIND EDATE ISNONTEXT FACT COUNTA FIXED EOMONTH ISNUMBER FLOOR COUNTBLANK LEFT HOUR ISTEXT INT MAX LEN MINUTE LN MAXA LOWER MONTH Logical LOG MIN MID NOW AND LOG10 MINA REPLACE SECOND IF MOD REPT TIME IFERROR MROUND RIGHT TIMEVALUE NOT PI SEARCH TODAY OR POWER SUBSTITUTE WEEKDAY FALSE QUOTIENT TRIM WEEKNUM TRUE RAND UPPER YEAR RANDBETWEEN VALUE YEARFRAC ROUND ROUNDDOWN ROUNDUP SIGN SQRT SUM SUMSQ TRUNC 7

8 Example: Functions over a Time Period TotalMTD (Expression, Date_Column [, SetFilter]) TotalQTD (Expression, Date_Column [, SetFilter]) TotalYTD (Expression, Date_Column [, SetFilter] [,YE_Date]) OpeningBalanceMonth (Expression, Date_Column [,SetFilter]) OpeningBalanceQuarter (Expression, Date_Column [,SetFilter]) OpeningBalanceYear (Expression, Date_Column [,SetFilter] [,YE_Date]) ClosingBalanceMonth (Expression, Date_Column [,SetFilter]) ClosingBalanceQuarter (Expression, Date_Column [,SetFilter]) ClosingBalanceYear (Expression, Date_Column [,SetFilter] [,YE_Date]) 8 8

9 9 1. Simplicity of DAX to Relate and Analyse Data

10 10 SharePoint 2010 BI Dashboards: PerformancePoint Services

11 PPS in SharePoint 2010 PerformancePoint Services in SharePoint 2010 improve over PerformancePoint Server 2007: SharePoint does all security, management, backup, respository of dashboard Decomposition Tree KPI Details Scorecard drilldown, dynamic hierarchies, calculated KPIs Dynamic, up-to-date filters for time intelligence SharePoint Dashboard Designer is smoother Better accessibility Analytic charts with value filtering and server-based conditional formatting 11 11

12 Monitoring with PPS Business users can build performance dashboards easily 12 12

13 Analytics with PPS Integration of KPIs and analytics Multidimensional slice and dice, drill-across, drill-to-detail, root-cause analysis, prediction and centralized business logic definitions No coding 13 13

14 Reporting and Consolidation in PPS Combine operational and financial data into one report No need to reconsolidate manually Dynamic and standard reports Consistent live reports published from Excel to Reporting Services and SharePoint 14 14

15 Dashboard Designer Workspace Browser Details pane 15 Workspace 15

16 Developing a Dashboard Choose a dashboard layout Assign elements to a dashboard zone Add filters Preview the dashboard Deploy to SharePoint 16 16

17 17 1. Building a Dashboard, Scorecard, and a KPI Using SharePoint Server PerformancePoint Services

18 18 Visualising BI with Microsoft Visio and SharePoint 2010

19 Two Trends that Lead to The Messy Diagram 19

20 Data Visualization Fault Analysis Tree Color By Value Text Callouts Status Indicators Data Bars 20

21 Data Visualization Manufacturing Specialized Shapes 21

22 Strategy Maps Visualize PPS Scorecard data in context 22 22

23 23 Data Mining with SQL Server

24 What does Data Mining Do? Explores Your Data Finds Patterns Performs Predictions 24 24

25 Typical Uses Seek Profitable Customers Correct Data During ETL Understand Customer Needs Detect and Prevent Fraud Data Mining Anticipate Customer Churn Build Effective Marketing Campaigns Predict Sales & Inventory 25 25

26 Server Mining Architecture Deploy BIDS Excel Visio SSMS Excel/Visio/SSRS/Your App OLE DB/ADOMD/XMLA App Data Analysis Services Server Mining Model Data Mining Algorithm Data Source 26 26

27 Data Mining Techniques Algorithm Decision Trees Association Rules Clustering Naïve Bayes Sequence Clustering Time Series Neural Nets Linear Regression Logistic Regression Description Finds the odds of an outcome based on values in a training set Identifies relationships between cases Classifies cases into distinctive groups based on any attribute sets Clearly shows the differences in a particular variable for various data elements Groups or clusters data based on a sequence of previous events Analyzes and forecasts time-based data combining the powerof ARTXP (developed by Microsoft Research) for short-term predictionswith ARIMA (in SQL 2008) for long-term accuracy. Seeks to uncover non-intuitive relationships in data Determines the relationship between columns in order to predict an outcome Determines the relationship between columns in order to evaluate the probability that a column will contain a specific state 28 28

28 34 1. Association Rules for Market Basket Analysis 2. Automatic recommendation engine using DMX queries

29 Summary Advanced self-service analysis requires a rich expression language: DAX Team, and organisational BI dashboards and scorecards are easy to build using SharePoint 2010 Data Mining enables advanced pattern (correlation) discovery in your data 35 35

30 2010 Microsoft Corporation & Project Botticelli Ltd. All rights reserved. The information herein is for informational purposes only and represents the opinions and views of Project Botticelli and/or Rafal Lukawiecki. The material presented is not certain and may vary based on several factors. Microsoft makes no warranties, express, implied or statutory, as to the information in this presentation. Portions 2010 Project Botticelli Ltd & entire material 2010 Microsoft Corp. Some slides contain quotations from copyrighted materials by other authors, as individually attributed or as already covered by Microsoft Copyright ownerships. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Project Botticelli Ltd as of the date of this presentation. Because Project Botticelli & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee the accuracy of any information provided after the date of this presentation. Project Botticelli makes no warranties, express, implied or statutory, as to the information in this presentation. E&OE