DP-500: Microsoft Azure and Microsoft Power BI Online Training

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This intermediate DP-500 prepares learners to take full control of a data analytics solution at the largest possible scale using Microsoft Power BI and tools available in Microsoft Azure.

If you're at the point in your career where you're considering a job in data analytics solutions that work at the enterprise level, you may think the skills necessary to be excellent in the field come naturally to some people and not others. But that's not true – designing, creating, and deploying large data analytics solutions are skills you can learn and practice.

1 Govern a Data Landscape with Microsoft Purview

1 Introducing Microsoft Purview

2 The Point of Purview

3 Deploy the Purview Resource

4 Configure a User Assigned Managed Identity

5 Register and Scan Data

6 Browse and Edit Catalog Assets

2 Administer Power BI with Powershell and REST APIs

7 Automate Power BI Administration

8 A Primer on PowerShell

9 Login and Get Power BI Data

10 Change Power BI Admin Data

11 Prepare for REST API Administration

12 Use the REST API (with PowerShell)

3 Integrate Power BI into an Existing Infrastructure

13 Integrating Power BI In An Existing Infrastructure

14 Plan for Power BI Integration

15 Configure Capacity Settings

16 Deploy and Use an On-Premises Data Gateway

17 Connect to Azure Data Lake Storage Gen 2

18 Work with Azure Synapse Analytics Workspaces

4 Utilize Source Control with Power BI Resources

19 Introducing Source Control in Analytics

20 The Github Crash Course

21 Using OneDrive for Version Control

22 Extract a Data Model

23 Leveraging Source Control in Azure Synapse

5 Deploy and Manage Datasets Using XMLA Endpoints

24 Introducing the XMLA Endpoint

25 The Point of the XMLA Endpoint (and APIs)

26 XMLA Endpoint Governance and Management

27 Querying and Processing with SSMS

28 Deploying Data Models with Tabular Editor 3

29 Connecting to XMLA with DAX Studio

30 Schema Compare and Deployment with ALM Toolkit

6 Implement Power BI Deployment Pipelines

31 Introducing Power BI Pipelines

32 How Pipelines Work

33 Create the Premium Workspaces

34 Deploy a Report through Production

35 Manage Deployment Options

36 Automate Pipelines with Azure DevOps

37 Summarizing Power BI Pipelines

7 Understand ETL and Data Warehouse Concepts

38 Introducing Data Warehouse Concepts

39 Data Warehouse Designs

40 ETL Concepts

41 Other Data Warehouse Resources

8 Implement, Load, and Query a Dedicated SQL Pool in Azure Synapse

42 Introducing Managing a Dedicated SQL Pool

43 Create Tables

44 Stage Data into Staging Tables

45 Load Data into a Dimension Table

46 Query Data in a Data Warehouse

47 Summarizing Data Warehouse Implementation

9 Query Data with Serverless SQL Pools

48 Introducing Querying with Serverless SQL Pools

49 Understand the Point of SQL Pools

50 Perform a Basic Serverless Query

51 Query JSON Files

52 Query Into a Filepath

53 Create a Database of External Sources

10 Query and Visualize Data Using Apache Spark in Azure Synapse

54 Introducing Apache Spark Pools

55 Deploy an Apache Spark pool

56 Perform a basic Pyspark Query

57 Define a Schema and Filter Query Results

58 Create a Catalog

59 Query Data with Apache Spark

60 Visualize Data in the Results Pane

11 Use the ML PREDICT T-SQL Function

61 Introducing the PREDICT Function

62 Set Up an ML Dev Environment

63 Generate the ONNX File

64 Load the Model into the Data Warehouse

65 Load the Data into the Data Warehouse

66 Use the PREDICT T-SQL Function

12 Query Advanced Data Sources using Power BI

67 Introducing Advanced Data Source Querying in Power BI

68 A Primer on JSON Data

69 Connect to and Query JSON Files

70 Connect to an API

71 Connect to Parquet Files

72 Set Up a ML Model

73 Consume the ML Model in Power Query

74 Deploy and Refresh the Model

13 Understand Enterprise Data Model Scalability Concepts

75 Understanding Data Model Scalability Designs

76 Understand Your Storage Mode Options

77 The Import Storage Mode

78 The DirectQuery Storage Mode

79 The Composite Storage Mode

80 Designing with Scalability in Mind

14 Deploy Power BI Dataflows

81 Introducing Power BI Dataflows

82 How Dataflows Work

83 Deploy a Dataflow

84 Set up Refresh Schedules

85 Edit and Add Additional Datasources

86 Maintaining and Endorsing Dataflows

15 Optimize Power Query and Report Performance

87 Introducing Power Query Optimization

88 Power Query Diagnostic Tracing

89 Report Analyzer

90 Tracing with SQL Profiler

91 Premium Capacity Metrics App

92 Fix Native Queries

93 Remove AutoDate

16 Create Calculation Groups in Tabular Editor

94 Introducing Calculation Groups

95 Understand the Problem with Measures

96 Explore Calculation Groups

97 Create Calculated Items

98 Clean Up the Calculation Group

99 Summarizing Calculation Groups

100 Challenge- Work Through Your Own Lab-

17 Create Queries, Functions, and Parameters by using the Power Query Advanced Editor

101 Introducing M in the Advanced Editor

102 Understand the Advanced Editor Syntax

103 Create a Basic Function

104 Use a Built-In Number Function

105 Create a Function with Conditions

106 Create a Table Function

107 Utilize Parameters

18 Implement Row and Object Level Security

108 Introducing Row and Object Level Security

109 Understand Row and Object Level Security

110 Implement Fixed Row Level Security

111 Implement Dynamic Row Level Security

112 DirectQuery Row Level Security Considerations

113 Implement Object Level Security

19 Leverage DirectQuery and Composite Data Models

114 Introducing DirectQuery

115 Pros and Cons of DirectQuery - Part 1

116 Pros and Cons of DirectQuery - Part 2

117 Basic DirectQuery Refresher

118 Reduce the Query Workload

119 Configure Dashboard Refresh Intervals

120 Use Composite Models

121 Summarizing DirectQuery

20 Optimize Data Models Using Third-Party Tools

122 Introducing Data Model Optimizations with Third Party Tools

123 Performance Analyzer

124 Understand VertiPaq Engine - Part 1

125 Understand VertiPaq Engine - Part 2

126 DAX Studio Server Timings

127 Model Metrics

128 Best Practices Analyzer in Tabular Editor

129 Summarizing Data Model Optimization

21 Use Advanced Visuals in Power BI

130 Introducing Advanced Power BI Visuals

131 Visual Best Practices

132 Use Themes

133 Implement Personalized Views

134 Implement Perspectives

135 Create R Visuals

136 Create Python Visuals

22 Create Power BI Paginated Reports

137 Introducing Power BI Paginated Reports

138 Before You Begin...

139 Connecting to a Data Source

140 Creating a Dataset

141 Creating a Table Visual

142 Using Parameters

143 Adding Charts to the Visual

144 Deploying a Paginated Report to Power BI

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مدرس: Knox Hutchinson