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E-raamat: Tabular Modeling in Microsoft SQL Server Analysis Services

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  • Formaat: 512 pages
  • Sari: Developer Reference
  • Ilmumisaeg: 12-Apr-2017
  • Kirjastus: Microsoft Press
  • Keel: eng
  • ISBN-13: 9781509302901
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Tabular Modeling in Microsoft SQL Server Analysis ServicesSuurem pilt
  • Formaat: 512 pages
  • Sari: Developer Reference
  • Ilmumisaeg: 12-Apr-2017
  • Kirjastus: Microsoft Press
  • Keel: eng
  • ISBN-13: 9781509302901
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With SQL Server Analysis Services 2016, Microsoft has dramatically upgraded its Tabular approach to business intelligence data modeling, making Tabular the easiest and best solution for most new projects. In this book, two world-renowned experts in Microsoft data modeling and analysis cover all you need to know to create complete BI solutions with these powerful new tools.

 

Marco Russo and Alberto Ferrari walk you step-by-step through creating powerful data models, and then illuminate advanced features such as optimization, deployment, and scalability.

 

Tabular Modeling in Microsoft SQL Server Analysis Services will be indispensable for everyone moving to Analysis Services Tabular, regardless of their previous experience with tabular-style models or with Microsoft's older Analysis Services offerings. It will also be an essential follow-up for every reader of the authors' highly-praised Microsoft SQL Server 2012 Analysis Services: The BISM Tabular Model.

Foreword xix
Introduction xxi
Chapter 1 Introducing the tabular model 1(22)
Semantic models in Analysis Services
1(2)
What is Analysis Services and why should I use it?
1(1)
A short history of Analysis Services
2(1)
Understanding Tabular and Multidimensional
3(5)
The tabular model
3(2)
The multidimensional model
5(2)
Why have two models?
7(1)
The future of Analysis Services
8(1)
Azure Analysis Services
8(1)
Choosing the right model for your project
8(6)
Licensing
9(1)
Upgrading from previous versions of Analysis Services
10(1)
Ease of use
10(1)
Compatibility with Power Pivot
10(1)
Compatibility with Power BI
10(1)
Query performance characteristics
10(1)
Processing performance characteristics
11(1)
Hardware considerations
11(1)
Real-time BI
12(1)
Client tools
12(1)
Feature comparison
13(1)
Understanding DAX and MDX
14(2)
The DAX language
15(1)
The MDX language
15(1)
Choosing the query language for Tabular
16(1)
Introduction to Tabular calculation engines
16(3)
Introduction to VertiPaq
17(1)
Introduction to DirectQuery
18(1)
Tabular model compatibility level (1200 vs. 110x)
19(1)
Analysis Services and Power BI
20(1)
Summary
21(2)
Chapter 2 Getting started with the tabular model 23(60)
Setting up a development environment
23(10)
Components of a development environment
23(3)
Licensing
26(1)
Installation process
26(7)
Working with SQL Server Data Tools
33(10)
Creating a new project
33(2)
Configuring a new project
35(5)
Importing from Power Pivot
40(1)
Importing from Power BI
41(1)
Importing a Deployed Project from Analysis Services
41(1)
Contents of a tabular project
42(1)
Building a simple tabular model
43(16)
Loading data into tables
44(10)
Working in the diagram view
54(4)
Navigating in Tabular Model Explorer
58(1)
Deploying a tabular model
59(1)
Querying tabular models with Excel
60(11)
Connecting to a tabular model
60(4)
Using PivotTables
64(1)
Using slicers
65(2)
Sorting and filtering rows and columns
67(3)
Using Excel cube formulas
70(1)
Querying tabular models with Power BI Desktop
71(7)
Creating a connection to a tabular model
71(2)
Building a basic Power BI report
73(1)
Adding charts and slicers
74(2)
Interacting with a report
76(2)
Working with SQL Server Management Studio
78(4)
Importing from Power Pivot
80(1)
Importing from Power BI Desktop
81(1)
Using DAX Studio as an alternative to SSMS
81(1)
Summary
82(1)
Chapter 3 Loading data inside Tabular 83(36)
Understanding data sources
83(2)
Understanding impersonation
85(1)
Understanding server-side and client-side credentials
86(1)
Working with big tables
87(1)
Loading from SQL Server
88(7)
Loading from a list of tables
90(3)
Loading from a SQL query
93(1)
Loading from views
94(1)
Opening existing connections
95(1)
Loading from Access
96(1)
Loading from Analysis Services
97(4)
Using the MDX editor
98(1)
Loading from a tabular database
99(2)
Loading from an Excel file
101(2)
Loading from a text file
103(2)
Loading from the clipboard
105(2)
Loading from a Reporting Services report
107(7)
Loading reports by using the report data source
108(4)
Loading reports by using data feeds
112(2)
Loading from a data feed
114(2)
Loading from SharePoint
116(1)
Choosing the right data-loading method
117(1)
Summary
118(1)
Chapter 4 Introducing calculations in DAX 119(22)
Introduction to the DAX language
119(13)
DAX syntax
120(1)
DAX data types
121(3)
DAX operators
124(1)
Column reference and measures reference
125(1)
Aggregate functions
126(1)
Table functions
126(1)
Evaluation context
127(2)
CALCULATE and CALCULATETABLE
129(3)
Variables
132(1)
Measures
132(1)
Calculated columns
133(2)
Calculated tables
135(1)
Writing queries in DAX
136(2)
Formatting DAX code
138(2)
DAX Formatter, DAX Studio, and DAX Editor
139(1)
Summary
140(1)
Chapter 5 Building hierarchies 141(18)
Basic hierarchies
141(7)
What are hierarchies?
141(2)
When to build hierarchies
143(1)
Building hierarchies
143(1)
Hierarchy design best practices
144(1)
Hierarchies spanning multiple tables
145(2)
Natural and unnatural hierarchies
147(1)
Parent-child hierarchies
148(10)
What are parent-child hierarchies?
148(1)
Configuring parent-child hierarchies
149(5)
Unary operators
154(4)
Summary
158(1)
Chapter 6 Data modeling in Tabular 159(34)
Understanding different data-modeling techniques
159(3)
Using the OLTP database
161(1)
Working with dimensional models
162(7)
Working with slowly changing dimensions
163(3)
Working with degenerate dimensions
166(1)
Using snapshot fact tables
167(2)
Using views to decouple from the database
169(1)
Relationship types
170(13)
Cardinality of relationships
172(4)
Filter propagation in relationships
176(4)
Active state of relationships
180(2)
Implementing relationships in DAX
182(1)
Normalization versus denormalization
183(4)
Calculated tables versus an external ETL
187(4)
Circular reference using calculated tables
189(2)
Summary
191(2)
Chapter 7 Tabular Model Scripting Language (TMSL) 193(24)
Defining objects in TMSL
193(19)
The Model object
195(3)
The DataSource object
198(1)
The Table object
199(7)
The Relationship object
206(1)
The Perspective object
207(1)
The Culture object
208(2)
The Role object
210(2)
TMSL commands
212(3)
Object operations in TMSL
212(2)
Data-refresh and database-management operations in TMSL
214(1)
Scripting in TMSL
214(1)
Summary
215(2)
Chapter 8 The tabular presentation layer 217(34)
Setting metadata for a Date table
217(1)
Naming, sorting, and formatting
218(10)
Naming objects
219(1)
Hiding columns and measures
220(1)
Organizing measures and columns
221(1)
Sorting column data
222(3)
Formatting
225(3)
Perspectives
228(2)
Power View-related properties
230(4)
Default field set
231(1)
Table behavior properties
232(2)
Key performance indicators
234(3)
Translations
237(10)
Creating a translation file
238(2)
Writing translated names in a translation file
240(1)
Choosing an editor for translation files
241(2)
Importing a translation file
243(1)
Testing translations using a client tool
244(2)
Removing a translation
246(1)
Best practices using translations
246(1)
Selecting culture and collation in a tabular model
247(3)
Changing culture and collation using an integrated workspace
249(1)
Changing culture and collation using a workspace server
249(1)
Summary
250(1)
Chapter 9 Using DirectQuery 251(18)
Configuring DirectQuery
252(9)
Setting DirectQuery in a development environment
252(6)
Setting DirectQuery after deployment
258(3)
Limitations in tabular models for DirectQuery
261(5)
Supported data sources
261(1)
Restrictions for data sources
262(1)
Restrictions for data modeling
262(1)
Restrictions for DAX formulas
262(2)
Restrictions for MDX formulas
264(1)
Tuning query limit
264(2)
Choosing between DirectQuery and VertiPaq
266(1)
Summary
267(2)
Chapter 10 Security 269(32)
User authentication
269(3)
Connecting to Analysis Services from outside a domain
270(1)
Kerberos and the double-hop problem
270(2)
Roles
272(3)
Creating database roles
272(2)
Membership of multiple roles
274(1)
Administrative security
275(2)
Granting permission through the server administrator role
275(1)
Granting database roles and administrative permissions
276(1)
Data security
277(13)
Basic data security
277(2)
Testing security roles
279(4)
Advanced row-filter expressions
283(5)
Security in calculated columns and calculated tables
288(1)
Using a permissions table
289(1)
Evaluating the impact of data security on performance
290(1)
Creating dynamic security
290(5)
DAX functions for dynamic security
290(1)
Implementing dynamic security by using CUSTOMDATA
291(2)
Implementing dynamic security by using USERNAME
293(2)
Security in DirectQuery
295(3)
Security and impersonation with DirectQuery
295(2)
Row-level security on SQL Server earlier than 2016
297(1)
Monitoring security
298(2)
Summary
300(1)
Chapter 11 Processing and partitioning tabular models 301(46)
Automating deployment to a production server
301(1)
Table partitioning
302(9)
Defining a partitioning strategy
302(3)
Defining partitions for a table in a tabular model
305(4)
Managing partitions for a table
309(2)
Processing options
311(13)
Available processing options
312(5)
Defining a processing strategy
317(3)
Executing processing
320(4)
Processing automation
324(14)
Using TMSL commands
324(7)
Using SQL Server Integration Services
331(3)
Using Analysis Management Objects (AMO) and Tabular Object Model (TOM)
334(2)
Using PowerShell
336(2)
Sample processing scripts
338(7)
Processing a database
338(1)
Processing tables
339(1)
Processing partitions
340(1)
Rolling partitions
341(4)
Summary
345(2)
Chapter 12 Inside VertiPaq 347(26)
Understanding VertiPaq structures
347(13)
Understanding column storage
348(3)
Value encoding versus hash encoding
351(3)
Run-length encoding
354(2)
Controlling column encoding
356(1)
Hierarchies and relationships
357(1)
Segmentation and partitioning
358(2)
Reading VertiPaq internal metadata
360(6)
Using DMVs for VertiPaq memory usage
360(1)
Interpreting VertiPaq Analyzer reports
361(5)
Memory usage in VertiPaq
366(3)
Data memory usage
366(1)
Processing memory usage
367(1)
Querying memory usage
368(1)
Understanding processing options
369(3)
What happens during processing
369(2)
Available processing options
371(1)
Summary
372(1)
Chapter 13 Interfacing with Tabular 373(22)
Introducing the AMO and TOM libraries
373(8)
Introducing AMOs
374(2)
Introducing the TOM
376(5)
Introducing the TMSL commands
381(2)
Creating a database programmatically
383(3)
Automating data refresh and partitioning
386(1)
Analyzing metadata
387(2)
Manipulating a data model
389(2)
Automating project deployment
391(3)
Copying the same database on different servers
391(1)
Deploying a model.bim file by choosing a database and server name
392(2)
Summary
394(1)
Chapter 14 Monitoring and tuning a Tabular service 395(30)
Finding the Analysis Services process
395(2)
Resources consumed by Analysis Services
397(3)
CPU
397(1)
Memory
398(2)
I/O operations
400(1)
Understanding memory configuration
400(5)
Using memory-related performance counters
405(4)
Using dynamic management views
409(3)
Interesting DMVs to monitor a Tabular service
411(1)
Automating monitoring info and logs acquisition
412(6)
Performance counters
412(1)
SQL Server Profiler
413(4)
ASTrace
417(1)
Flight Recorder
417(1)
Extended Events
417(1)
Other commercial tools
418(1)
Monitoring data refresh (process)
418(4)
Monitoring queries
422(2)
Summary
424(1)
Chapter 15 Optimizing tabular models 425(28)
Optimizing data memory usage
425(13)
Removing unused columns
425(1)
Reducing dictionary size
426(3)
Choosing a data type
429(2)
Reducing a database size by choosing the sort order
431(2)
Improving encoding and bit sizing
433(1)
Optimizing large dimensions
434(4)
Designing tabular models for large databases
438(6)
Optimizing compression by splitting columns
438(1)
Optimizing the process time of large tables
439(1)
Aggregating fact tables at different granularities
440(4)
Designing tabular models for near-real-time solutions
444(7)
Choosing between DirectQuery and VertiPaq
445(1)
Using partitions
446(2)
Reducing recalculation time
448(2)
Managing lock during process
450(1)
Summary
451(2)
Chapter 16 Choosing hardware and virtualization 453(14)
Hardware sizing
453(8)
CPU clock and model
454(3)
Memory speed and size
457(1)
NUMA architecture
458(2)
Disk and I/O
460(1)
Hardware requirements for DirectQuery
460(1)
Optimizing hardware configuration
461(2)
Power settings
461(1)
Hyper-threading
462(1)
NUMA settings
463(1)
Virtualization
463(1)
Splitting NUMA nodes on different VMs
464(1)
Committing memory to VMs
464(1)
Scalability of an SSAS Tabular solution
464(2)
Scalability for a single database (large size)
465(1)
Scalability for large user workload
465(1)
Summary
466(1)
Index 467
Marco Russo and Alberto Ferrari are the founders of sqlbi.com, where they regularly publish articles about Microsoft Power Pivot, Power BI, DAX, and SQL Server Analysis Services. Russo and Ferrari have worked with Analysis Services since the first version in 1999. Both Russo and Ferrari provide consultancy and mentoring on business intelligence (BI). They are also frequent speakers at major international conferences, including Microsoft Ignite, PASS Summit, and SQLBits.
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