DAX Patterns, 2nd Edition
- Length: 418 pages
- Edition: 2
- Language: English
- Publisher: SQLBI Corp.
- Publication Date: 2020-07-28
- ISBN-10: 1735365203
- ISBN-13: 9781735365206
- Sales Rank: #226372 (See Top 100 Books)
A pattern is a general, reusable solution to a frequent or common challenge. This book is the second edition of the most comprehensive collection of ready-to-use solutions in DAX, that you can use in Microsoft Power BI, Analysis Services Tabular, and Power Pivot for Excel.The book includes the following patterns: Time-related calculations, Standard time-related calculations, Month-related calculations, Week-related calculations, Custom time-related calculations, Comparing different time periods, Semi-additive calculations, Cumulative total, Parameter table, Static segmentation, Dynamic segmentation, ABC classification, New and returning customers, Related distinct count, Events in progress, Ranking, Hierarchies, Parent-child hierarchies, Like-for-like comparison, Transition matrix, Survey, Basket analysis, Currency conversion, Budget.
Introduction Why we published this book How to use this book Prerequisites Acknowledgments Chapter 1 Time-related calculations Chapter 2 Standard time-related calculations Introduction to time intelligence calculations What are standard DAX time intelligence functions Disabling the Auto Date/Time Limitations of standard time intelligence functions Building a Date table Controlling the visualization in future dates Naming convention Computing period-to-date totals Year-to-date total Quarter-to-date total Month-to-date total Computing period-over-period growth Year-over-year growth Quarter-over-quarter growth Month-over-month growth Period-over-period growth Computing period-to-date growth Year-over-year-to-date growth Quarter-over-quarter-to-date growth Month-over-month-to-date growth Comparing period-to-date with previous full period Year-to-date over the full previous year Quarter-to-date over full previous quarter Month-to-date over full previous month Using moving annual total calculations Moving annual total Moving annual total growth Moving averages Moving average 30 days Moving average 3 months Moving average 1 year Filtering other date attributes Chapter 3 Month-related calculations Introduction to month-related time intelligence calculations Building a Date table Naming convention Computing period-to-date totals Year-to-date total Quarter-to-date total Computing period-over-period growth Year-over-year growth Quarter-over-quarter growth Month-over-month growth Period-over-period growth Computing period-to-date growth Year-over-year-to-date growth Quarter-over-quarter-to-date growth Comparing period-to-date with a previous full period Year-to-date over the full previous year Quarter-to-date over full previous quarter Using moving annual total calculations Moving annual total Moving annual total growth Moving averages Moving average 3 months Moving average 1 year Managing years with more than 12 months Chapter 4 Week-related calculations Introduction to week-related time intelligence calculations Building a Date table Understanding filter-safe columns Controlling the visualization in future dates Naming convention Computing period-to-date totals Year-to-date total Quarter-to-date total Month-to-date total Week-to-date total Computing period-over-period growth Year-over-year growth Quarter-over-quarter growth Week-over-week growth Period-over-period growth Computing period-to-date growth Year-over-year-to-date growth Quarter-over-quarter-to-date growth Week-over-week-to-date growth Comparing period-to-date with previous full period Year-to-date over the full previous year Quarter-to-date over the full previous quarter Week-to-date over the full previous week Using moving annual total calculations Moving annual total Moving annual total growth Moving averages Moving average 4 weeks Moving average 1 quarter Moving average 1 year Chapter 5 Custom time-related calculations Introduction to custom time intelligence calculations Building a Date table Understanding filter-safe columns Controlling the visualization on future dates Naming convention Computing period-to-date totals Year-to-date total Quarter-to-date total Month-to-date total Computing period-over-period growth Year-over-year growth Quarter-over-quarter growth Month-over-month growth Period-over-period growth Computing period-to-date growth Year-over-year-to-date growth Quarter-over-quarter-to-date growth Month-over-month-to-date growth Comparing period-to-date with a previous full period Year-to-date over the full previous year Quarter-to-date over the full previous quarter Month-to-date over the full previous month Using moving annual total calculations Moving annual total Moving annual total growth Moving averages Moving average 30 days Moving average 1 year Chapter 6 Comparing different time periods Pattern description Chapter 7 Semi-additive calculations Introduction First and last date First and last date with data First and last date by customer Opening and closing balance Growth in period Chapter 8 Cumulative total Basic scenario Cumulative total on columns that can be sorted Chapter 9 Parameter table Changing the scale of a measure Multiple independent parameters Multiple dependent parameters Selecting top N products dynamically Chapter 10 Static segmentation Basic pattern Price ranges by category Price ranges on large tables Chapter 11 Dynamic segmentation Basic pattern Clustering by product growth Clustering by best status Chapter 12 ABC classification Static ABC classification Snapshot ABC classification Dynamic ABC classification Finding the ABC class Chapter 13 New and returning customers Introduction Pattern description Internal measures External measures How to use pattern measures Internal measures New customers Lost customers Temporarily-lost customers Recovered customers Returning customers Dynamic absolute Internal measures New customers Lost customers Temporarily-lost customers Recovered customers Returning customers Generic dynamic pattern (dynamic by category) Internal measures New customers Lost customers Temporarily-lost customers Recovered customers Returning customers Snapshot absolute Creating the derived snapshot table in DAX Chapter 14 Related distinct count Pattern description Chapter 15 Events in progress Definition of events in progress Open orders Open orders with snapshot Chapter 16 Ranking Static ranking Dynamic ranking Showing the top 3 products by category Chapter 17 Hierarchies Detecting the current level of a hierarchy Percentage of parent node Chapter 18 Parent-child hierarchies Introduction Basic Parent-child pattern Chart of accounts hierarchy Security pattern for a parent-child hierarchy Chapter 19 Like-for-like comparison Introduction Same store sales with snapshot Same store sales without snapshot Chapter 20 Transition matrix Introduction Static transition matrix Dynamic transition matrix Chapter 21 Survey Pattern description Chapter 22 Basket analysis Defining association rules metrics # # And # Total # Both % Support % Confidence Lift Sample reports Basic pattern example Optimized pattern example Chapter 23 Currency conversion Multiple source currencies, single reporting currency Single source currency, multiple reporting currencies Multiple source currencies, multiple reporting currencies Chapter 24 Budget Introduction The data model Business choices Allocation based on the previous year Dismissed products do not contribute to the allocation New products have their own forecast amount Products can be dismissed or introduced on a yearly basis Forecast allocation Showing actuals and forecasts on the same chart About the authors
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