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Definitive Guide to DAX, The: Business intelligence with Microsoft Excel, SQL Server Analysis Services, and Power BI

Definitive Guide to DAX, The: Business intelligence with Microsoft Excel, SQL Server Analysis Services, and Power BI

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  • Copyright 2016
  • Dimensions: 7-3/8" x 9"
  • Edition: 1st
  • eBook (Watermarked)
  • ISBN-10: 0-7356-9839-2
  • ISBN-13: 978-0-7356-9839-0

This comprehensive and authoritative guide will teach you the DAX language for business intelligence, data modeling, and analytics. Leading Microsoft BI consultants Marco Russo and Alberto Ferrari help you master everything from table functions through advanced code and model optimization. You’ll learn exactly what happens under the hood when you run a DAX expression, how DAX behaves differently from other languages, and how to use this knowledge to write fast, robust code. If you want to leverage all of DAX’s remarkable power and flexibility, this no-compromise “deep dive” is exactly what you need.
Perform powerful data analysis with DAX for Microsoft SQL Server Analysis Services, Excel, and Power BI

  • Master core DAX concepts, including calculated columns, measures, and error handling
  • Understand evaluation contexts and the CALCULATE and CALCULATETABLE functions
  • Perform time-based calculations: YTD, MTD, previous year, working days, and more
  • Work with expanded tables, complex functions, and elaborate DAX expressions
  • Perform calculations over hierarchies, including parent/child hierarchies
  • Use DAX to express diverse and unusual relationships
  • Measure DAX query performance with SQL Server Profiler and DAX Studio

Sample Content

Table of Contents

Foreword    xvii
Introduction    xix
Chapter 1: What is DAX?    1

Understanding the data model    1
Understanding the direction of a relationship    3
DAX for Excel users    5
Cells versus tables    5
Excel and DAX: Two functional languages    8
Using iterators    8
DAX requires some theory    8
DAX for SQL developers    9
Understanding relationship handling    9
DAX is a functional language    10
DAX as a programming and querying language    11
Subqueries and conditions in DAX and SQL    12
DAX for MDX developers    13
Multidimensional vs. Tabular    13
DAX as a programming and querying language    13
Hierarchies    14
Leaf-level calculations    15
Chapter 2: Introducing DAX    17
Understanding DAX calculations    17
DAX data types    18
DAX operators    21
Understanding calculated columns and measures    22
Calculated columns    22
Measures    23
Variables    26
Handling errors in DAX expressions    26
Conversion errors    26
Arithmetical operations errors    27
Intercepting errors    30
Formatting DAX code    32
Common DAX functions    35
Aggregate functions    35
Logical functions    37
Information functions    39
Mathematical functions    39
Trigonometric functions    40
Text functions    40
Conversion functions    41
Date and time functions    42
Relational functions    42
Chapter 3: Using basic table functions    45
Introducing table functions    45
EVALUATE syntax    47
Using table expressions    50
Understanding FILTER    51
Understanding ALL, ALLEXCEPT, and ALLNOBLANKROW    54
Understanding VALUES and DISTINCT    58
Using VALUES as a scalar value    59
Chapter 4: Understanding evaluation contexts    61
Introduction to evaluation contexts    62
Understanding the row context    66
Testing your evaluation context understanding    67
Using SUM in a calculated column    67
Using columns in a measure    68
Creating a row context with iterators    69
Using the EARLIER function    70
Understanding FILTER, ALL, and context interactions    74
Working with many tables    77
Row contexts and relationships    78
Filter context and relationships    80
Introducing VALUES    84
Evaluation contexts recap    88
Creating a parameter table    89
Chapter 5: Understanding CALCULATE and CALCULATETABLE    93
Understanding CALCULATE    93
Understanding the filter context    95
Introducing CALCULATE    98
CALCULATE examples    101
Filtering a single column    101
Filtering with complex conditions    106
Understanding context transition    111
Understanding context transition with measures    114
How many rows are visible after context transition?    116
Understanding evaluation order of context transition    117
Variables and evaluation contexts    118
Understanding circular dependencies    119
CALCULATE rules    122
Introducing ALLSELECTED    123
Understanding USERELATIONSHIP    125
Chapter 6: DAX examples    129
Computing ratios and percentages    129
Computing cumulative totals    132
Using ABC (Pareto) classification    136
Computing sales per day and working day    143
Computing differences in working days    150
Computing static moving averages    151
Chapter 7: Time intelligence calculations    155
Introduction to time intelligence    155
Building a Date table    156
Working with multiple dates    160
Handling multiple relationships to the Date table    161
Handling multiple Date tables    162
Introduction to time intelligence    164
Using Mark as Date Table    166
Aggregating and comparing over time    168
Year-to-date, quarter-to-date, month-to-date    168
Computing periods from prior periods    171
Computing difference over previous periods    174
Computing the moving annual total    175
Closing balance over time    178
Semi-additive measures    178
Advanced time intelligence    188
Understanding periods to date    189
Understanding DATEADD    191
Understanding FIRSTDATE and LASTDATE    196
Using drillthrough with time intelligence    200
Custom calendars    200
Working with weeks    201
Custom year-to-date, quarter-to-date, month-to-date    204
Computing over noncontiguous periods    206
Custom comparison between periods    210
Chapter 8: Statistical functions    213
Using RANKX    213
Common pitfalls using RANKX    216
Using RANK.EQ    219
Computing average and moving average    220
Computing variance and standard deviation    222
Computing median and percentiles    223
Computing interests    225
Alternative implementation of PRODUCT and GEOMEAN    226
Using internal rate of return (XIRR)    227
Using net present value (XNPV)    228
Using Excel statistical functions    229
Sampling by using the SAMPLE function    230
Chapter 9: Advanced table functions    233
Understanding EVALUATE    233
Using VAR in EVALUATE    235
Understanding filter functions    236
Using TOPN    239
Understanding projection functions    241
Using ADDCOLUMNS    241
Using ROW    247
Understanding lineage and relationships    248
Understanding grouping/joining functions    250
Using SUMMARIZE    250
Using GROUPBY    261
Understanding set functions    267
Using CROSSJOIN    267
Using UNION    269
Using INTERSECT    272
Using EXCEPT    274
Understanding utility functions    278
Using CONTAINS    278
Using LOOKUPVALUE    280
Using ISONORAFTER    284
Chapter 10: Advanced evaluation context    285
Understanding ALLSELECTED    285
Understanding KEEPFILTERS    294
Understanding AutoExists    304
Understanding expanded tables    307
Difference between table expansion and filtering    315
Redefining the filter context    316
Understanding filter context intersection    318
Understanding filter context overwrite    320
Understanding arbitrarily shaped filters    321
Understanding the ALL function    326
Understanding lineage    329
Using advanced SetFilter    331
Learning and mastering evaluation contexts    338
Chapter 11: Handling hierarchies    339
Computing percentages over hierarchies     339
Handling parent-child hierarchies    346
Handling unary operators    358
Implementing unary operators by using DAX    359
Chapter 12: Advanced relationships    367
Using calculated physical relationships    367
Computing multiple-column relationships    367
Computing static segmentation    369
Using virtual relationships    371
Using dynamic segmentation    371
Many-to-many relationships    373
Using relationships with different granularities    378
Differences between physical and virtual relationships    381
Finding missing relationships    382
Computing number of products not sold    383
Computing new and returning customers    384
Examples of complex relationships    386
Performing currency conversion    386
Frequent itemset search    392
Chapter 13: The VertiPaq engine    399
Understanding database processing    400
Introduction to columnar databases    400
Understanding VertiPaq compression    403
Understanding value encoding    404
Understanding dictionary encoding    405
Understanding Run Length Encoding (RLE)    406
Understanding re-encoding    409
Finding the best sort order    409
Understanding hierarchies and relationships    410
Understanding segmentation and partitioning    412
Using Dynamic Management Views    413
Understanding materialization    417
Choosing hardware for VertiPaq    421
Can you choose hardware?    421
Set hardware priorities    421
CPU model    422
Memory speed    423
Number of cores    423
Memory size    424
Disk I/O and paging    424
Conclusions    424
Chapter 14: Optimizing data models    425
Gathering information about the data model    425
Denormalization    434
Columns cardinality    442
Handling date and time    443
Calculated columns    447
Optimizing complex filters with Boolean calculated columns    450
Choosing the right columns to store    451
Optimizing column storage    453
Column split optimization    453
Optimizing high cardinality columns    454
Optimizing drill-through attributes    455
Chapter 15: Analyzing DAX query plans    457
Introducing the DAX query engine    457
Understanding the formula engine    458
Understanding the storage engine (VertiPaq)    459
Introducing DAX query plans    459
Logical query plan    460
Physical query plan    461
Storage engine query    462
Capturing profiling information    463
Using the SQL Server Profiler    463
Using DAX Studio    467
Reading storage engine queries    470
Introducing xmSQL syntax    470
Understanding scan time    477
Understanding DISTINCTCOUNT internals    479
Understanding parallelism and datacache    480
Understanding the VertiPaq cache    481
Understanding CallbackDataID    483
Reading query plans    488
Chapter 16: Optimizing DAX    495
Defining optimization strategy    496
Identifying a single DAX expression to optimize    496
Creating a reproduction query    499
Analyzing server timings and query plan information    500
Identifying bottlenecks in the storage engine or formula engine    503
Optimizing bottlenecks in the storage engine    504
Choosing ADDCOLUMNS vs. SUMMARIZE    505
Reducing CallbackDataID impact    509
Optimizing filter conditions    512
Optimizing IF conditions    513
Optimizing cardinality    515
Optimizing nested iterators    517
Optimizing bottlenecks in the formula engine    522
Creating repro in MDX    527
Reducing materialization    528
Optimizing complex bottlenecks    532
Index    537


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