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1. Introduction
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1.1 IntroductionLecture1.1
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1.2 PrerequisitesLecture1.2
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2. Download software, demos, and book
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3 .Introducing optimization with examples
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3.1 Introducing optimization with examplesLecture3.1
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3.2 IntroductionLecture3.2
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3.3 Optimizing DAXLecture3.3
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3.4 Optimizing the modelLecture3.4
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3.5 ConclusionsLecture3.5
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3.6 Links to external contentLecture3.6
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4. Introducing the Tabular query architecture
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4.1 .Introducing the Tabular query architectureLecture4.1
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4.2 IntroductionLecture4.2
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4.3 Introducing the formula engineLecture4.3
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4.4 Introducing VertiPaq and DirectQuery architecturesLecture4.4
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4.5 Introducing the VertiPaq storage engineLecture4.5
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4.6 Introducing the DirectQuery over SQL storage engineLecture4.6
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4.7 Introducing DirectQuery over ASLecture4.7
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4.8 Introducing data islands and cross-island query resolutionLecture4.8
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4.9 Different types of modelsLecture4.9
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5. Using the Power BI Desktop performance analyzer
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5.1 Using the Power BI Desktop performance analyzerLecture5.1
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5.2 IntroductionLecture5.2
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5.3 Running Performance AnalyzerLecture5.3
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5.4 Understanding the numbers reported by Performance AnalyzerLecture5.4
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5.5 Optimizing queries or measures?Lecture5.5
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5.6 What can be optimizedLecture5.6
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5.7 Saving performance dataLecture5.7
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5.8 ConclusionsLecture5.8
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6. Using DAX Studio
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6.1 Using DAX StudioLecture6.1
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6.2 IntroductionLecture6.2
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6.3 Installing DAX StudioLecture6.3
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6.4 Introducing the metrics of a databaseLecture6.4
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6.5 Introducing All QueriesLecture6.5
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6.6 Capturing Excel queries (MDX)Lecture6.6
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6.7 Introducing Load Performance DataLecture6.7
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6.8 Introducing Query Plan and Server TimingsLecture6.8
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6.9 Links to external contentLecture6.9
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7. Introducing query plans
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7.1 Introducing query plansLecture7.1
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7.2 IntroductionLecture7.2
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7.3 Introducing the logical query planLecture7.3
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7.4 Introducing the physical query planLecture7.4
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7.5 Introducing storage engine queriesLecture7.5
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7.6 Query plans in DirectQueryLecture7.6
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7.7 ConclusionsLecture7.7
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8. Understanding the DAX Formula Engine
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8.1 Understanding the DAX Formula EngineLecture8.1
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8.2 IntroductionLecture8.2
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8.3 Understanding datacachesLecture8.3
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8.4 Understanding materializationLecture8.4
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8.5 Understanding callbacksLecture8.5
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8.6 Formula engine with different storage enginesLecture8.6
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8.7 Understanding vertical fusionLecture8.7
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8.8 Understanding horizontal fusionLecture8.8
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8.9A Sales of best productsLecture8.9
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8.9B Top three colorsLecture8.10
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8.10 Measuring performanceLecture8.11
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8.11 Gathering important timings from the query planLecture8.12
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8.12 Analyzing query plans and timingsLecture8.13
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8.13 ConclusionsLecture8.14
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9. Understanding query plans
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9.1 Understanding query plansLecture9.1
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9.2 IntroductionLecture9.2
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9.3 Query plan structureLecture9.3
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9.4 Query plan operator typesLecture9.4
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9.5 Interactions between the formula engine and the storage engineLecture9.5
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9.6 Common query plan operatorsLecture9.6
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9.7A Comparing SUM versus SUMXLecture9.7
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9.7B IF versus IF.EAGERLecture9.8
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9.7C Filtering with DAX versus using relationshipsLecture9.9
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9.7D Understanding SWITCH optimizationLecture9.10
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9.8 ConclusionsLecture9.11
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10. Optimizing the formula engine
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10.1 Optimizing the formula engineLecture10.1
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10.2 IntroductionLecture10.2
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10.3 Optimizing datacache useLecture10.3
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10.4 Sales of best productsLecture10.4
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10.5 Running total of sales and ABC analysisLecture10.5
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10.6 Year-over-year customer growth as a percentageLecture10.6
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10.7 ConclusionsLecture10.7
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11. Understanding the VertiPaq engine
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11.1 Understanding the VertiPaq engineLecture11.1
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11.2 IntroductionLecture11.2
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11.3 Using VertiPaq AnalyzerLecture11.3
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11.4 Tabular data typesLecture11.4
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11.5 Introduction to the VertiPaq columnar databaseLecture11.5
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11.6 Understanding VertiPaq compressionLecture11.6
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11.7 Understanding segmentation and partitioningLecture11.7
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11.8 Understanding the importance of sortingLecture11.8
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11.9 Understanding VertiPaq relationshipsLecture11.9
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11.10 Understanding attribute hierarchiesLecture11.10
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11.11A Sales amount versus quantity and net priceLecture11.11
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11.11B Storing currency conversion dataLecture11.12
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11.11C Date time versus date and timeLecture11.13
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11.12 ConclusionsLecture11.14
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12. Understanding VertiPaq relationships
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12.1 Understanding VertiPaq relationshipsLecture12.1
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12.2 IntroductionLecture12.2
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12.3 Regular, unidirectional one-to-many relationshipsLecture12.3
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12.4 Regular, bidirectional one-to-many relationshipsLecture12.4
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12.5 Regular, one-to-one relationshipsLecture12.5
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12.6 Limited, many-to-many cardinality relationshipsLecture12.6
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12.7 ConclusionsLecture12.7
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13. Analyzing VertiPaq storage engine queries
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13.1 Analyzing VertiPaq storage engine queriesLecture13.1
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13.2 IntroductionLecture13.2
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13.3 Analyzing simple xmSQL queriesLecture13.3
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13.4 Introducing basic VertiPaq functionalitiesLecture13.4
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13.5 Introducing batchesLecture13.5
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13.6 Understanding internal and external SE queriesLecture13.6
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13.7 Understanding distinct count in xmSQLLecture13.7
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13.8A Introducing VertiPaq joinsLecture13.8
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13.8B Introducing bitmap indexesLecture13.9
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13.8C Introducing reverse joinsLecture13.10
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13.9A Understanding VertiCalc and callbacksLecture13.11
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13.9B Understanding CallbackDataIDLecture13.12
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13.9C Understanding EncodeCallbackLecture13.13
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13.9D Understanding LogAbsValueCallbackLecture13.14
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13.9E Understanding RoundValueCallbackLecture13.15
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13.9F Understanding MinMaxColumnPositionCallbackLecture13.16
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13.9G Understanding CondLecture13.17
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13.10 Understanding the VertiPaq cacheLecture13.18
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13.11 Choosing the correct data type for VertiPaq calculationsLecture13.19
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13.12 ConclusionsLecture13.20
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14. Moving and applying filters to tables
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14.1 Optimizing common DAX constructsLecture14.1
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14.2 IntroductionLecture14.2
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14.3A Different filters in CALCULATELecture14.3
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14.3B Analyzing single-column filtersLecture14.4
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14.3C Analyzing multiple-column filtersLecture14.5
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14.3D Analyzing filters over multiple tablesLecture14.6
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14.4 Understanding sparse or dense filtersLecture14.7
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14.5 Filter columns, not tablesLecture14.8
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14.6A Modeling many-to-many relationshipsLecture14.9
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14.6B Testing the bidirectional modelLecture14.10
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14.6C Testing the star modelLecture14.11
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14.6D Testing the snake modelLecture14.12
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14.6E Testing the advanced snake modelLecture14.13
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14.7 ConclusionsLecture14.14
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15. Optimization examples for VertiPaq
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15.1 Optimization examples for VertiPaqLecture15.1
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15.2 IntroductionLecture15.2
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15.3 Optimizing nested iterationsLecture15.3
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15.4 Understanding the effect of context transitionLecture15.4
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15.5 Different ways of performing a distinct countLecture15.5
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15.6 Optimizing LASTDATE calculationsLecture15.6
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15.7 Avoid using SUMMARIZE and clusteringLecture15.7
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15.8 Optimizing division by checking for zeroesLecture15.8
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15.9 Reducing the extent of the search by removing blanksLecture15.9
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15.10 Optimizing time intelligence calculationsLecture15.10
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15.11 Distinct count over large cardinality columns’Lecture15.11
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15.12 ConclusionsLecture15.12
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16. Understanding security optimizations
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16.1 Understanding security optimizationsLecture16.1
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16.2 IntroductionLecture16.2
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16.3 Testing security conditions and their performance impactLecture16.3
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16.4 Understanding when and where security is enforcedLecture16.4
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16.5 Understanding cached bitmap indexes and embedded filtersLecture16.5
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16.6 Optimizing dynamic securityLecture16.6
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16.7 Optimizing static security on the fact tableLecture16.7
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16.8 Optimizing dynamic security on the fact tableLecture16.8
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16.9 ConclusionsLecture16.9
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17. Understanding DirectQuery over SQL
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17.1 IntroductionLecture17.1
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17.2 Reading SQL code in this courseLecture17.2
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17.3 Reading the numbers in DAX StudioLecture17.3
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17.4 Callback operationsLecture17.4
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17.5 Calculated tablesLecture17.5
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17.6 Calculated columnsLecture17.6
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17.7 How caching works in DirectQuery over SQLLecture17.7
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17.8 Understanding latency to send queries to the remote serverLecture17.8
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17.9 Max number of rows in a data cacheLecture17.9
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17.10A Regular one-to-many relationshipsLecture17.10
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17.10B Limited many-to-many relationshipsLecture17.11
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17.10C One-to-one relationshipsLecture17.12
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17.11 DirectQuery over SQL max parallel queriesLecture17.13
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17.12 Using different data islandsLecture17.14
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17.13 Introducing aggregations and hybrid tablesLecture17.15
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17.14 ConclusionsLecture17.16
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18. Optimizing DirectQuery over SQL
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18.1 IntroductionLecture18.1
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18.1A IntroductionLecture18.2
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18.1B Designing indexesLecture18.3
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18.1C Using columnstore indexesLecture18.4
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18.1D Choosing column data typesLecture18.5
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18.1E Do not use Power Query transformationsLecture18.6
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18.2A Choosing the best data type for relationshipsLecture18.7
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18.2B Relying on referential integrityLecture18.8
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18.2C Using COMBINEVALUES to implement multi-column relationshipsLecture18.9
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18.3A Introducing aggregationsLecture18.10
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18.3B Introducing VertiPaq aggregation and Dual storage modeLecture18.11
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18.3C Designing aggregations for simple calculationsLecture18.12
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18.3D Designing aggregations for row-level calculationLecture18.13
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18.3E Designing aggregations for distinct countLecture18.14
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18.3F Aggregations are not VertiPaq aliases of DirectQuery tablesLecture18.15
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18.3G Manually activating aggregations in DAXLecture18.16
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18.3H Using automatic aggregationsLecture18.17
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18.4A Introducing hybrid tablesLecture18.18
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18.4B Hybrid tables and distinct countLecture18.19
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18.4C Creating hybrid tables with incremental refreshLecture18.20
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18.5 ConclusionsLecture18.21
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19. Optimization examples for DirectQuery
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19.1 IntroductionLecture19.1
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19.2 Optimizing LASTDATE calculationsLecture19.2
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19.3 Optimizing division by checking for zeroesLecture19.3
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19.4 Optimizing time intelligence calculationsLecture19.4
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19.5 Computing distinct countsLecture19.5
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19.6 ConclusionsLecture19.6
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20. Conclusion
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