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MCA Microsoft Certified Associate Azure Data Engineer Study Guide - Perkins, Benjamin

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        Présentation Mca Microsoft Certified Associate Azure Data Engineer Study Guide de Perkins, Benjamin Format Broché

         - Livre

        Livre - Perkins, Benjamin - 01/09/2023 - Broché - Langue : Anglais

        . .

      • Auteur(s) : Perkins, Benjamin
      • Editeur : John Wiley & Sons Inc
      • Langue : Anglais
      • Parution : 01/09/2023
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 1008
      • Expédition : 1832
      • Dimensions : 23.4 x 18.6 x 5.3
      • ISBN : 1119885426



      • Résumé :

        Introduction xxvii

        Part I?Azure Data Engineer Certification and Azure Products 1

        Chapter 1?Gaining the Azure Data Engineer Associate Certification 3

        The Journey to Certification 7

        How to Pass Exam DP- 203 8

        Understanding the Exam Expectations and Requirements 9

        Use Azure Daily 17

        Read Azure Articles to Stay Current 17

        Have an Understanding of All Azure Products 20

        Azure Product Name Recognition 21

        Azure Data Analytics 23

        Azure Synapse Analytics 23

        Azure Databricks 26

        Azure HDInsight 28

        Azure Analysis Services 30

        Azure Data Factory 31

        Azure Event Hubs 33

        Azure Stream Analytics 34

        Other Products 35

        Azure Storage Products 36

        Azure Data Lake Storage 37

        Azure Storage 40

        Other Products 42

        Azure Databases 43

        Azure Cosmos DB 43

        Azure SQL Server Products 46

        Additional Azure Databases 46

        Other Products 47

        Azure Security 48

        Azure Active Directory 48

        Role- Based Access Control 51

        Attribute- Based Access Control 53

        Azure Key Vault 53

        Other Products 55

        Azure Networking 56

        Virtual Networks 56

        Other Products 59

        Azure Compute 59

        Azure Virtual Machines 59

        Azure Virtual Machine Scale Sets 60

        Azure App Service Web Apps 60

        Azure Functions 60

        Azure Batch 60

        Azure Management and Governance 60

        Azure Monitor 61

        Azure Purview 61

        Azure Policy 62

        Azure Blueprints (Preview) 62

        Azure Lighthouse 62

        Azure Cost Management and Billing 62

        Other Products 63

        Summary 64

        Exam Essentials 64

        Review Questions 66

        Chapter 2 CREATE DATABASE dbName...

        Biographie:

        ABOUT THE AUTHOR

        Benjamin Perkins is currently employed at Microsoft in Munich, Germany, as a Senior Escalation Engineer on the Azure team. He is a C# programming expert and cloud engineer who has been working professionally in the IT industry for almost three decades. His roles in IT have spanned the entire spectrum including programmer, system architect, technical support engineer, team leader, and mid-level management. While employed at Hewlett-Packard and Compaq Computer Corporation, he received numerous awards, degrees, and certifications....

        Sommaire:
        GO 69

        The Brainjammer 70

        A Historical Look at Data 71

        Variety 73

        Velocity 74

        Volume 74

        Data Locations 74

        Data File Formats 75

        Data Structures, Types, and Concepts 83

        Data Structures 83

        Data Types and Management 92

        Data Concepts 95

        Data Programming and Querying for Data Engineers 125

        Data Programming 126

        Querying Data 143

        Understanding Big Data Processing 169

        Big Data Stages 169

        Etl, Elt, Eltl 174

        Analytics Types 175

        Big Data Layers 176

        Summary 177

        Exam Essentials 177

        Review Questions 179

        Part II Design and Implement Data Storage 181

        Chapter 3 Data Sources and Ingestion 183

        Where Does Data Come From? 185

        Design a Data Storage Structure 189

        Design an Azure Data Lake Solution 190

        Recommended File Types for Storage 198

        Recommended File Types for Analytical Queries 199

        Design for Efficient Querying 200

        Design for Data Pruning 203

        Design a Folder Structure That Represents the Levels of Data Transformation 203

        Design a Distribution Strategy 205

        Design a Data Archiving Solution 206

        Design a Partition Strategy 207

        Design a Partition Strategy for Files 209

        Design a Partition Strategy for Analytical Workloads 210

        Design a Partition Strategy for Efficiency and Performance 211

        Design a Partition Strategy for Azure Synapse Analytics 211

        Identify When Partitioning Is Needed in Azure Data Lake Storage Gen 2 212

        Design the Serving/Data Exploration Layer 213

        Design Star Schemas 214

        Design Slowly Changing Dimensions 215

        Design a Dimensional Hierarchy 219

        Design a Solution for Temporal Data 220

        Design for Incremental Loading 222

        Design Analytical Stores 223

        Design Metastores in Azure Synapse Analytics and Azure Databricks 224

        The Ingestion of Data into a Pipeline 228

        Azure Synapse Analytics 228

        Azure Data Factory 268

        Azure Databricks 275

        Event Hubs and IoT Hub 301

        Azure Stream Analytics 303

        Apache Kafka for HDInsight 314

        Migrating and Moving Data 316

        Summary 317

        Exam Essentials 317

        Review Questions 319

        Chapter 4 The Storage of Data 321

        Implement Physical Data Storage Structures 322

        Implement Compression 322

        Implement Partitioning 325

        Implement Sharding 328

        Implement Different Table Geometries with Azure Synapse Analytics Pools 329

        Implement Data Redundancy 331

        Implement Distributions 341

        Implement Data Archiving 342

        Azure Synapse Analytics Develop Hub 346

        Implement Logical Data Structures 360

        Build a Temporal Data Solution 361

        Build a Slowly Changing Dimension 365

        Build a Logical Folder Structure 368

        Build External Tables 369

        Implement File and Folder Structures for Efficient Querying and Data Pruning 372

        Implement a Partition Strategy 375

        Implement a Partition Strategy for Files 376

        Implement a Partition Strategy for Analytical Workloads 377

        Implement a Partition Strategy for Streaming Workloads 378

        Implement a Partition Strategy for Azure Synapse Analytics 378

        Design and Implement the Data Exploration Layer 379

        Deliver Data in a Relational Star Schema 379

        Deliver Data in Parquet Files 385

        Maintain Metadata 386

        Implement a Dimensional Hierarchy 386

        Create and Execute Queries by Using a Compute Solution That Leverages SQL Serverless and Spark Cluster 388

        Recommend Azure Synapse Analytics Database Templates 389

        Implement ...

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