power pivot for techies
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MAKING BUSINESS INTELLIGENT www.pragmaticworks.com
Power Pivot For TechiesPragmatic Works
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Class Logistics
• Dan Clark (dclark@pragmaticworks.com)• Make it Interactive!!!• Mute when not talking to class.• Let me know if sound or video cuts out.• Have Fun – This is cool stuff!!!
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Introductions
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Agenda - Day 1
• Introduction to PowerPivot• Importing Data• Creating the Data Model• Calculations with DAX• Lab Setup
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Agenda - Day 2
• Creating Measures• Time Intelligence• PivotTables• PivotCharts
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Agenda - Day 3
• Tabular Data Models in SSAS• Understanding Context with DAX• Advanced Data Analysis• Managing and Securing Tabular Models
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Module 1: Introduction to PowerPivot
• Why use PowerPivot?• Vertipaq Engine• Installing PowerPivot• Exploring Data with PowerPivot
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Why use PowerPivot?
• Self Service BI• Fast Performance• Familiar Excel
Interface• Data Analysis
Expressions (DAX) • Integrate Data• Integrate with
SharePoint
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The Vertipaq Engine• Fast Performance• Columnar Database • Data Compression
• In-memory Storage• Calculations on the Fly• Table Model
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Installing PowerPivot
• Free Add-in to Excel 2010• 32bit version – supports 2GB files• 64bit version – supports 4GB files• Windows XP SP3 – 32bit only• Windows 7 – 32bit and 64bit versions
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Exploring Data with PowerPivot
• Pivot Tables• Fields and Values• Filtering and Slicing• Measures • KPIs• Hierarchies• Pivot Charts
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Hands On Lab: Installing andExploring Data with PowerPivot
http://pragmaticworks.com/PowerPivotForTechies.zip
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Module 2Importing Data into PowerPivot
• Databases• Files• SSAS Cubes• Data Feeds• Refreshing Data
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Importing Data from a DatabaseThe Table Import Wizard
• Tables and Views• Previewing• Queries• Stored Procedures
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Importing Data from a File
• Importing from Excel– Launches Table Import Wizard– Select Tables (sheets)– Data Preview
• Text File Imports Single Table–No Query option
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Importing Data from an SSAS Cube
• SSAS 2005 or greater• MDX Query (Designer Available)• Result is Flattened to Table
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Importing Data from a Data Feed
• XML Data Streams • Online Data Source• B to B EDI• Data Feed in Atom Format • Use Table Import Wizard• Provide Web Address
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Refreshing Data in PowerPivot
• Data is Point in Time• Manually Refresh Data– Automatic Recalculation Recommended
• Automatic Data Refresh – Published to SharePoint 2010– Scheduled Data Refresh Managed by SharePoint
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Hands On Lab:Loading Data into PowerPivot
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Module 3: Creating the Data Model
• What is a Data Model?• Creating Table Relations• Denormalizing Data• Linked Tables• Creating Hierarchies
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What is a Data Model?
• Tables and Relations• Logical Model vs. Physical Model• Normalization vs. Denormalization• OLAP vs. OLTP• Facts and Dimensions
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Creating Table Relations
• Relationship Types– Active and Inactive
• Auto Relationship Detection– Verifying Auto Detection
• Manually Defining Relationships– Data Types– Concatenated Keys
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Denormalizing Data
• When to Denormalize• Denormalizing After Loading Data– Using the Related Function
• Denormalizing While Loading Data– Using SQL Queries– Table Joins– Using the Query Designer
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Linked Tables
• Table created in Excel• Linked to a Table in PowerPivot• Changes to Linked Tables Automatically
Reflect the Changes in PowerPivot.
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Hierarchies
• Organize Attributes• Natural Hierarchies
Year Quarter MonthCountry Region City
• Aids in Rolling up/Drilling down Analysis
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Hands On Lab: Updating a Data Model in PowerPivot
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Module 4: Creating Calculations with DAX
• Why DAX?• Calculated Columns• DAX Operators• Working with Text• Date and Time Functions• Conditional and Logical Functions• Miscellaneous Functions
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Why DAX?
• Easier Data Analysis • Larger User Base• Leverage Excel– Formula Syntax– PivotTables
• Simpler Relational Data Model– Based on Tables, Columns, and Relationships– No Complex Multidemensional Concepts
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Adding Calculated Columns
• Uses DAX Expressions• Populated When Defined• Uses in PivotTable – Row/Column Labels– Filters/Slicers
Data TypesWhole NumberDecimal NumberCurrencyTrue/False TextDate Binary
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DAX Operators
Type Symbol Use
Arithmetic operator + (plus sign) Addition– (minus sign) Subtraction Negation* (asterisk) Multiplication/ (forward slash) Division^ (caret) Exponentiation
Comparison operator = Equal to > Greater than < Less than >= Greater than or equal to <= Less than or equal to <> Not equal to
MarginPercent =[Margin]/[TotalCost]
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DAX Operators (Cont.)
Type Symbol UseText operator & (ampersand) Concatenates two values
Logical operator && (double ampersand) Creates an AND condition between two expressions.
|| (double pipe symbol) Creates an OR condition between two logical expressions.
! (NOT) Returns the complement of the condition defined by the expression that follows.
Parenthesis operator () precedence order and grouping of arguments
LastName=[FirstName] & " " & [LastName]
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Working with Text
• Formatting• Concatenating• Casing• Trimming
• Splitting• Searching• Replacing• Converting
CalendarWeekLabel ="Week" & "-" & Right([CalendarWeek],2)
FormatDate=FORMAT('Date'[Datekey],"dddd mmm-dd")
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Using Date and Time Functions
• Converting • Current Date and Time• Splitting Apart Dates• Week Number and Week Day• Maturity Dates• Elapsed Time
CalendarMonth =MONTH([Datekey])
Age =Year(NOW()) - Year([BirthDate])
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Using Conditional and Logical Functions
• Conditional Calculations• Testing for Multiple Conditions• Testing for Any Condition• Testing for Errors• Testing for Number or Text• Nesting Conditions• Blank Values
StoreSizeArea =IF([SellingAreaSize]>=1000,"Large","Small")
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Math Functions
• Ceiling• Log• Round• Random• Trunc
AdjustedPrice=CEILING([ProductPrice],0.05)
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Navigation Functions
• Getting a Value From a Related Table• Getting a Set of Values From a Related Table• Filtering Values from a Related Table
ProductCategory=Related('ProductCategory'[ProductCategoryName])
StoreCount=COUNTX(RELATEDTABLE(Store),Store[EntityKey])
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Hands on Lab: Adding Calculated Columns with DAX
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Module 5: Creating Measures with DAX
• Measures• Aggregation• Filter Context• Calculate Function• Miscellaneous Functions
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Measures
• Named Formulas • Defined in Measures Grid• Used in Values Area of PivotTable• Evaluated on the Fly• Evaluated Separately for Each Cell
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Filter Context• Applied by Filter Constraints• Row and Column Headers• Slicers and Filters• DAX Formula Filters
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Aggregation
• Aggregating a column– SUM, AVERAGE, COUNT, DISTINCTCOUNT, MIN,
MAX• Aggregating Expressions Over Rows– SUMX, AVERAGEX, COUNTX, MINX, MAXX
TotalSales:=SUM([SalesAmount])
TotalMargin:=SUMX(Sales,(Sales[SalesAmount]-Sales[TotalCost]))
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Using the Calculate Function
• Final Result is a single Value• Expression is Aggregate• SetFilter Modifies Filter Context– Boolean Expression– Table Expression
ResellerSales:=CALCULATE([TotalSales],Store[StoreType]="Reseller")
AllProductSales:=CALCULATE([TotalSales], ALL(Product))
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Miscellaneous Functions
• Rank– Ranks Value in List of
Values• TopN
– Returns Aggregate of Top or Bottom Values
SalesTotal =SUM(Sales[SalesAmount])
Bottom10ProductSales =SUMX(TOPN(10, Product, [SalesTotal], 1), [SalesTotal])
ColorRank:=RANKX(ALL(Product[ColorName]), [SalesTotal])
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Miscellaneous Functions Cont.
• USERRELATIONSHIP– Allows the Use of a Non-active Relationship– Used in Functions That Have a Filter Argument
• Values– Returns Valid Values for the Column– Based on Current Filter Context– Often Used in IF Function
USERELATIONSHIP(FactSales[ShipDateKey], ‘Date’[DateKey])
VALUES(Geography[RegionCountryName]) = “United States”
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Hands on Lab:Adding Measures with DAX
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Module 6: Incorporating Time Intelligence
• Creating Date Tables• Time Intelligence Functions• Comparing Data over Time• Semi-Additive Measures
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Creating Date Tables• One Row for Every Date• Span Range of Possible Dates• Import From Source or Create in
Excel• Mark as a Date Table in Model• Date Column Passed to Time
Intelligence Functions
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Time Intelligence Functions• Set of 35 Functions• Handles Both Calendar and Fiscal Years• Functions Returning a Single Date• Previous/Next Functions• To-date• Shifting Date Context
LNBDate:=LASTNONBLANK('Date'[Datekey],[BaseQty])
FIRSTDATE('Date'[Datekey])
DATEADD(Date[DateKey], -1, YEAR))
PREVIOUSMONTH(Date[DateKey])
DATESYTD(Date[DateKey])
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Time Intelligence (cont.)
• Evaluate Expressions Over a Period of Time• Evaluate Expressions for a Point in Time
YTDSales:=TOTALYTD([Sales],'Date'[Datekey])
=CLOSINGBALANCEMONTH(SUMX(Inventory,Inventory[UnitCost]*Inventory[UnitsOnHand]),Date[DateKey])
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Using Time Intelligence
• Comparing Data over Time– Year-to-Date– Year Over Year Growth– Using a Period Table
• Semi-additive Measures– Aggregated Using SUM Over Some Dimensions– Different Aggregation Over Other Dimensions (Date/Time)– Examples
• Balances • Inventory Levels
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Hands on Lab:Adding Time Intelligence
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Module 7: Working with PivotTables
• Pivot Table Fundamentals• Sorting, Filtering, and Formatting• Adding Calculations• Using Sets • Adding Banding
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PivotTable Fundamentals
• Field List– Values, Labels, Filters, and Slicers– Numeric Fields Default to Values– Text Fields Default to Labels– Hiding Fields and Tables
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Sorting, Filtering, and Formatting
• Sorting– Built in Sorting Options– Using Sort Lists
• Filtering– Label Filters– Value Filters– Showing Top Values
• Formatting– Using PivotTable Tools Design Tab– Conditional Formatting
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Adding Calculations
• Showing Values as % of Total• Ranking Values• Aggregating Values• Inserting Columns– Convert to Values– Convert to Cube Formulas
=CUBEVALUE("PowerPivot Data",$C7,E$6,Slicer_Year,Slicer_Quarter,Slicer_ResellerSize)
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Using Sets and Adding Banding
• Sets– Based on Rows or Columns– Appears in Set Folder After Tables– Use for Custom Sets Not Defined in Data Source
• Banding– Convert Continuous Values into Buckets• Age Ranges, Pricing, Income
– Use a Table Defining Band Ranges– Use Calculate Function to Select Band
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Hands on Lab:Building a PivotTable Report
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Module 8 - Visualizing Data
• PivotTable Visualization• Flattened PivotTable• Working With PivotCharts• Using Multiple Charts and Tables
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PivotTable Visualization
• Data Bars• Sparklines
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Flattened PivotTables
• Uses Standard Table Layout• Useful for Reports and Printing
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Working with PivotCharts
• Creates a Chart Sheet and a PivotTable Sheet
• PivotTable Provides Data for the Chart
• Popular Chart Types– Column, Pie, Bar, Line
• PivotChart Tools Tabs– Design, Layout, Format, Analyze
• Slicers Control Both Chart and Table
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Using Multiple Charts and Tables
• Using Predefined Layouts
• Slicers
• Adding PivotTables and Charts to Existing Layouts
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Hands on Lab: Visualizing the Data
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Module 9: Creating Tabular Data Models in SSAS
• Advantages of using Tabular Data Models• Installing SSAS Tabular Mode• SQL Server Data Tools• Creating Tabular Model Projects• Importing Data• Table Relations
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Advantages of using Tabular Data Models in SSAS
• Scalability• Manageability• Security• Development Tools
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Installing SSAS Tabular Mode
• Uses Vertipaq Engine• Needs Own Instance of SSAS• Server Mode Must be Tabular• Install SQL Server Data Tools
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Creating Tabular Model Projects in SQL Server Data Tools
• Project Templates • Designer Window– Similar to
PowerPivot• Error List• Property Windows• Tool Integration – DAX Editor– Source Control– Deployment Wizard
• Solution Explorer– Container for Project– .bim File Contains Database
Definition, Metadata, Copy and Pasted Data
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Importing Data
• Data Sources– Relational Databases– Analysis Service Cubes – Imported as Flattened Data– Excel Files– Power Pivot Workbook - Hosted on SharePoint– Text Files– Data Feeds – Atom Feeds, Reporting Services Reports
• Table Import Wizard– Same as PowerPivot
• Copy and Paste– 10,000 Row Limit– Tables can’t be Partitioned
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Table Relations
• Relate Tables Together by Common Column• Composite Keys not Supported– Use a Calculated Column
• Types– One-To-Many– One-To-One
• Table Import Wizard Detects Relationships Defined in Database
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Table Relations (Cont.)• Single Active Relationship Between Tables
– Default Used in DAX and Model– Ensures Non-ambiguous dependencies between tables.– Non-Active Relationship Can Exist and be used by DAX– Can Copy Table and Use as Active
• Example - Order Date and Ship Date
• One Relationship for Each Source Column– Source Column Cannot Participate in Multiple Relationships– Can Use Calculated Column to Copy Column
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Hands on Lab: Loading Data into a Tabular Model
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Module 10: DAX Context• Identifying the Row Context• Query and Filter Contexts• Functions that Alter Context• Context and Calculations
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Row Context
• Calculated column– Row Context Includes All Values in Current Row
• DAX Function that Iterates Over Rows• SUMX
• Multiple Tables– RELATED Function propagates Row Context
• Must be a Relationship Defined in the Model• Uses Active Relationship by Default• Propagates From the One Side to the Many Side
Discount = SALES[Price] * (1 - RELATED(CustomerDiscount[Discount]))
SalesCount = SUMX(RELATEDTABLE(Sales),Sales[OrderQuantity])
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Query and Filter Contexts
• Query Context– Established by the Row and Column Headers– Further Restricted by Filters and Slicers– Different For Each Cell
• Filter Context– Added When a Filter Constraint is Used– Alters the Query Context
SUMX(Filter(Sales,Sales[OrderQuantity]>5),SALES[SalesAmount])
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Functions That Alter the Context
• FILTER • DISTINCT• CALCULATE• CALCULATETABLE• ALL• ALLEXCEPT
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Functions That Alter the Context• ALLSELECTED
– Removes context filters from columns and rows– Retains all other context filters or explicit filters.
• KEEPFILTERS function– Filters Override any Existing Column Filter
• Hierarchies Filter Context is Cleared• Causes Problems Rolling Up the Data
– KEEPFILTERS Adds Filter Context to Existing Filters
SUMX (KEEPFILTERS (VALUES (Date[CalendarYear])), [TotalSales])
CALCULATE(SUM('ResellerSales'[SalesAmount]), ALLSELECTED())
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Context and Calculations
• CALCULATE and RELATEDTABLE convert Row Context to Filter Context
• Set Row Identifier in Table Properties– Avoids Circular Dependencies – Optimizes Calculations– Will Cause Memory Footprint to Increase– Avoid on Large Tables (Fact Table)
• CALCULATE Performs Better Than FILTER and RELATEDTABLE
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Hands On Lab - Exploring Row and Filter Contexts
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Module 11: Advanced Data Analysis
• Creating KPI’s• Parent – Child Relationships• Many to Many Relationships
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Creating KPI’s
• Used to Gauge Performance of a Value• Often used on a Business Scorecard• Usually Displayed in Graphical Format– Red, Yellow, Green
• Base Value– Defined by a Measure
• Target Value– Defined by Measure or Absolute Value
• Status Thresholds– Defined by Range Between a low and High Value
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Parent – Child Relationships• Table with a Self-referencing Relationship• Designed to Store Relationships
Between Records in the Same Table• DAX Can Materialize Implied Relationships• Used to Create Parent – Child Hierarchy
– Useful for • Organizational Structures• General Ledger Structures
• DAX Functions Exist for Navigating Path
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Many to Many Relationship
• Intermediate Table used to Join Tables• Not Supported by Model Designer• Simulated With DAX
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Manny To Many Relationships
• Example – Market Basket Analysis– Used to Analyze Customers
Who Purchased Two Sets of Products• Two Copies of the Product Table• Inactive Relationship Defined
Between Sales Table and Product Tables• Filter Customers Who Bought One Set of Products• Check if They Bought a Product From the Other
Set
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Hands on Lab: Creating KPIs and Parent-Child Hierarchies
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Module 12: Managing and Securing Tabular Data Models in SSAS
• Implementing Perspectives• Applying Role Based Security• Implementing Row Based Security• Creating and Processing Partitions• Deploying a Tabular Model
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Implementing Perspectives
• Define Viewable Subsets of a Model • Provide Business-Specific Viewpoints• Tables, Columns, and Measures are Defined as
Field Objects• Select the Viewable Fields for Each Perspective• Not Meant to be Used for Security• Tool for Providing a Better User Experience
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Applying Role Based Security
• Define Member Permissions for a Model• Membership is by Windows Username/Group• Permissions – Read
• Query Data (Based on Row Filters)
– Process • Can Run Processing Operations
– Administrator• Can Make Modifications to the Model Schema • Can Query All Data
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Implementing Row Based Security
• Row Filters Define Which Rows Can be Queried
• Row Filters are Defined Using DAX Formulas• Must Evaluate to a TRUE/FALSE Value• Row Filters Apply to the Specified Rows as
Well as Related Rows• Use the Filter, =FALSE(), to Deny Access to All
Rows For a Table
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Processing PartitionsOption Description
Add Adds new rows to a partition. Any affected calculated columns, relationships, user hierarchies, or internal engine structures (except table dictionaries) are recalculated.
Clear Drops all the data in a database, table, or partition.
Data Loads data into a partition or table.
Default Loads data into unprocessed partitions or tables. Any affected calculated columns, relationships, user hierarchies, or internal engine structures (except table dictionaries) are recalculated.
Full Loads data into all selected partitions or tables. Any affected calculated columns, relationships, user hierarchies, or internal engine structures (except table dictionaries) are recalculated.
Recalc For all tables in the database, recalculates calculated columns, rebuilds relationships. rebuilds user hierarchies, and rebuilds other internal engine structures.
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Deploying a Tabular Model
• Must Deploy to SSAS for Client Access• Connecting to Deployed Model– .bism Connection File in Sharepoint – Data connection directly from reporting client
• Microsoft Excel, Power View, Custom Applications
• Deployment Options– SQL Server Data Tools (SSDT)
• Set Deployment Properties• Server, Database, Cube Name, Processing
– Analysis Management Objects (AMO) Automation– Synchronize Database Wizard
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Hands On Lab: Securing a Tabular Model
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Resources
Web Siteshttp://technet.microsoft.com/en-us/library/gg399181.aspxhttp://powerpivot-info.comhttp://blogs.msdn.com/b/analysisservices/http://www.bidn.com
Books –http://www.amazon.com/Microsoft-PowerPivot-Excel-2010-Meaning/dp/0735640580http://www.amazon.com/gp/product/0071746854/
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