{"product_id":"mca-microsoft-certified-associate-azure-data-engineer-study-guide-exam-dp-203-paperback-softback-9781119885429","title":"MCA Microsoft Certified Associate Azure Data Engineer Study Guide; Exam DP-203 (Paperback \/ softback) 9781119885429","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eMCA Microsoft Certified Associate Azure Data Engineer Study Guide\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eExam DP-203\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eBenjamin Perkins (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781119885429, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePaperback \/ softback, published 6 September 2023\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e1008 pages\u003cbr\u003e23.9 x 19.3 x 6.6 cm, 1.383 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003ePrepare for the Azure Data Engineering certification—and an exciting new career in analytics—with this must-have study aide\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn the \u003ci\u003eMCA Microsoft Certified Associate Azure Data Engineer Study Guide: Exam DP-203\u003c\/i\u003e, accomplished data engineer and tech educator Benjamin Perkins delivers a hands-on, practical guide to preparing for the challenging Azure Data Engineer certification and for a new career in an exciting and growing field of tech.\u003c\/p\u003e \u003cp\u003eIn the book, you’ll explore all the objectives covered on the DP-203 exam while learning the job roles and responsibilities of a newly minted Azure data engineer. From integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions, you’ll get up to speed quickly and efficiently with Sybex’s easy-to-use study aids and tools.\u003c\/p\u003e \u003cp\u003eThis Study Guide also offers:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eCareer-ready advice for anyone hoping to ace their first data engineering job interview and excel in their first day in the field\u003c\/li\u003e \u003cli\u003eIndispensable tips and tricks to familiarize yourself with the DP-203 exam structure and help reduce test anxiety\u003c\/li\u003e \u003cli\u003eComplimentary access to Sybex’s expansive online study tools, accessible across multiple devices, and offering access to hundreds of bonus practice questions, electronic flashcards, and a searchable, digital glossary of key terms\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eA one-of-a-kind study aid designed to help you get straight to the crucial material you need to succeed on the exam and on the job, the \u003ci\u003eMCA Microsoft Certified Associate Azure Data Engineer Study Guide: Exam DP-203\u003c\/i\u003e belongs on the bookshelves of anyone hoping to increase their data analytics skills, advance their data engineering career with an in-demand certification, or hoping to make a career change into a popular new area of tech.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eIntroduction xxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I \u003cb\u003eAzure Data Engineer Certification and Azure Products 1\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Gaining the Azure Data Engineer Associate Certification 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Journey to Certification 7\u003c\/p\u003e \u003cp\u003eHow to Pass Exam DP- 203 8\u003c\/p\u003e \u003cp\u003eUnderstanding the Exam Expectations and Requirements 9\u003c\/p\u003e \u003cp\u003eUse Azure Daily 17\u003c\/p\u003e \u003cp\u003eRead Azure Articles to Stay Current 17\u003c\/p\u003e \u003cp\u003eHave an Understanding of All Azure Products 20\u003c\/p\u003e \u003cp\u003eAzure Product Name Recognition 21\u003c\/p\u003e \u003cp\u003eAzure Data Analytics 23\u003c\/p\u003e \u003cp\u003eAzure Synapse Analytics 23\u003c\/p\u003e \u003cp\u003eAzure Databricks 26\u003c\/p\u003e \u003cp\u003eAzure HDInsight 28\u003c\/p\u003e \u003cp\u003eAzure Analysis Services 30\u003c\/p\u003e \u003cp\u003eAzure Data Factory 31\u003c\/p\u003e \u003cp\u003eAzure Event Hubs 33\u003c\/p\u003e \u003cp\u003eAzure Stream Analytics 34\u003c\/p\u003e \u003cp\u003eOther Products 35\u003c\/p\u003e \u003cp\u003eAzure Storage Products 36\u003c\/p\u003e \u003cp\u003eAzure Data Lake Storage 37\u003c\/p\u003e \u003cp\u003eAzure Storage 40\u003c\/p\u003e \u003cp\u003eOther Products 42\u003c\/p\u003e \u003cp\u003eAzure Databases 43\u003c\/p\u003e \u003cp\u003eAzure Cosmos DB 43\u003c\/p\u003e \u003cp\u003eAzure SQL Server Products 46\u003c\/p\u003e \u003cp\u003eAdditional Azure Databases 46\u003c\/p\u003e \u003cp\u003eOther Products 47\u003c\/p\u003e \u003cp\u003eAzure Security 48\u003c\/p\u003e \u003cp\u003eAzure Active Directory 48\u003c\/p\u003e \u003cp\u003eRole- Based Access Control 51\u003c\/p\u003e \u003cp\u003eAttribute- Based Access Control 53\u003c\/p\u003e \u003cp\u003eAzure Key Vault 53\u003c\/p\u003e \u003cp\u003eOther Products 55\u003c\/p\u003e \u003cp\u003eAzure Networking 56\u003c\/p\u003e \u003cp\u003eVirtual Networks 56\u003c\/p\u003e \u003cp\u003eOther Products 59\u003c\/p\u003e \u003cp\u003eAzure Compute 59\u003c\/p\u003e \u003cp\u003eAzure Virtual Machines 59\u003c\/p\u003e \u003cp\u003eAzure Virtual Machine Scale Sets 60\u003c\/p\u003e \u003cp\u003eAzure App Service Web Apps 60\u003c\/p\u003e \u003cp\u003eAzure Functions 60\u003c\/p\u003e \u003cp\u003eAzure Batch 60\u003c\/p\u003e \u003cp\u003eAzure Management and Governance 60\u003c\/p\u003e \u003cp\u003eAzure Monitor 61\u003c\/p\u003e \u003cp\u003eAzure Purview 61\u003c\/p\u003e \u003cp\u003eAzure Policy 62\u003c\/p\u003e \u003cp\u003eAzure Blueprints (Preview) 62\u003c\/p\u003e \u003cp\u003eAzure Lighthouse 62\u003c\/p\u003e \u003cp\u003eAzure Cost Management and Billing 62\u003c\/p\u003e \u003cp\u003eOther Products 63\u003c\/p\u003e \u003cp\u003eSummary 64\u003c\/p\u003e \u003cp\u003eExam Essentials 64\u003c\/p\u003e \u003cp\u003eReview Questions 66\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 CREATE DATABASE dbName; GO 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Brainjammer 70\u003c\/p\u003e \u003cp\u003eA Historical Look at Data 71\u003c\/p\u003e \u003cp\u003eVariety 73\u003c\/p\u003e \u003cp\u003eVelocity 74\u003c\/p\u003e \u003cp\u003eVolume 74\u003c\/p\u003e \u003cp\u003eData Locations 74\u003c\/p\u003e \u003cp\u003eData File Formats 75\u003c\/p\u003e \u003cp\u003eData Structures, Types, and Concepts 83\u003c\/p\u003e \u003cp\u003eData Structures 83\u003c\/p\u003e \u003cp\u003eData Types and Management 92\u003c\/p\u003e \u003cp\u003eData Concepts 95\u003c\/p\u003e \u003cp\u003eData Programming and Querying for Data Engineers 125\u003c\/p\u003e \u003cp\u003eData Programming 126\u003c\/p\u003e \u003cp\u003eQuerying Data 143\u003c\/p\u003e \u003cp\u003eUnderstanding Big Data Processing 169\u003c\/p\u003e \u003cp\u003eBig Data Stages 169\u003c\/p\u003e \u003cp\u003eEtl, Elt, Eltl 174\u003c\/p\u003e \u003cp\u003eAnalytics Types 175\u003c\/p\u003e \u003cp\u003eBig Data Layers 176\u003c\/p\u003e \u003cp\u003eSummary 177\u003c\/p\u003e \u003cp\u003eExam Essentials 177\u003c\/p\u003e \u003cp\u003eReview Questions 179\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Design and Implement Data Storage 181\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Data Sources and Ingestion 183\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhere Does Data Come From? 185\u003c\/p\u003e \u003cp\u003eDesign a Data Storage Structure 189\u003c\/p\u003e \u003cp\u003eDesign an Azure Data Lake Solution 190\u003c\/p\u003e \u003cp\u003eRecommended File Types for Storage 198\u003c\/p\u003e \u003cp\u003eRecommended File Types for Analytical Queries 199\u003c\/p\u003e \u003cp\u003eDesign for Efficient Querying 200\u003c\/p\u003e \u003cp\u003eDesign for Data Pruning 203\u003c\/p\u003e \u003cp\u003eDesign a Folder Structure That Represents the Levels of Data Transformation 203\u003c\/p\u003e \u003cp\u003eDesign a Distribution Strategy 205\u003c\/p\u003e \u003cp\u003eDesign a Data Archiving Solution 206\u003c\/p\u003e \u003cp\u003eDesign a Partition Strategy 207\u003c\/p\u003e \u003cp\u003eDesign a Partition Strategy for Files 209\u003c\/p\u003e \u003cp\u003eDesign a Partition Strategy for Analytical Workloads 210\u003c\/p\u003e \u003cp\u003eDesign a Partition Strategy for Efficiency and Performance 211\u003c\/p\u003e \u003cp\u003eDesign a Partition Strategy for Azure Synapse Analytics 211\u003c\/p\u003e \u003cp\u003eIdentify When Partitioning Is Needed in Azure Data Lake Storage Gen 2 212\u003c\/p\u003e \u003cp\u003eDesign the Serving\/Data Exploration Layer 213\u003c\/p\u003e \u003cp\u003eDesign Star Schemas 214\u003c\/p\u003e \u003cp\u003eDesign Slowly Changing Dimensions 215\u003c\/p\u003e \u003cp\u003eDesign a Dimensional Hierarchy 219\u003c\/p\u003e \u003cp\u003eDesign a Solution for Temporal Data 220\u003c\/p\u003e \u003cp\u003eDesign for Incremental Loading 222\u003c\/p\u003e \u003cp\u003eDesign Analytical Stores 223\u003c\/p\u003e \u003cp\u003eDesign Metastores in Azure Synapse Analytics and Azure Databricks 224\u003c\/p\u003e \u003cp\u003eThe Ingestion of Data into a Pipeline 228\u003c\/p\u003e \u003cp\u003eAzure Synapse Analytics 228\u003c\/p\u003e \u003cp\u003eAzure Data Factory 268\u003c\/p\u003e \u003cp\u003eAzure Databricks 275\u003c\/p\u003e \u003cp\u003eEvent Hubs and IoT Hub 301\u003c\/p\u003e \u003cp\u003eAzure Stream Analytics 303\u003c\/p\u003e \u003cp\u003eApache Kafka for HDInsight 314\u003c\/p\u003e \u003cp\u003eMigrating and Moving Data 316\u003c\/p\u003e \u003cp\u003eSummary 317\u003c\/p\u003e \u003cp\u003eExam Essentials 317\u003c\/p\u003e \u003cp\u003eReview Questions 319\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 The Storage of Data 321\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eImplement Physical Data Storage Structures 322\u003c\/p\u003e \u003cp\u003eImplement Compression 322\u003c\/p\u003e \u003cp\u003eImplement Partitioning 325\u003c\/p\u003e \u003cp\u003eImplement Sharding 328\u003c\/p\u003e \u003cp\u003eImplement Different Table Geometries with Azure Synapse Analytics Pools 329\u003c\/p\u003e \u003cp\u003eImplement Data Redundancy 331\u003c\/p\u003e \u003cp\u003eImplement Distributions 341\u003c\/p\u003e \u003cp\u003eImplement Data Archiving 342\u003c\/p\u003e \u003cp\u003eAzure Synapse Analytics Develop Hub 346\u003c\/p\u003e \u003cp\u003eImplement Logical Data Structures 360\u003c\/p\u003e \u003cp\u003eBuild a Temporal Data Solution 361\u003c\/p\u003e \u003cp\u003eBuild a Slowly Changing Dimension 365\u003c\/p\u003e \u003cp\u003eBuild a Logical Folder Structure 368\u003c\/p\u003e \u003cp\u003eBuild External Tables 369\u003c\/p\u003e \u003cp\u003eImplement File and Folder Structures for Efficient Querying and Data Pruning 372\u003c\/p\u003e \u003cp\u003eImplement a Partition Strategy 375\u003c\/p\u003e \u003cp\u003eImplement a Partition Strategy for Files 376\u003c\/p\u003e \u003cp\u003eImplement a Partition Strategy for Analytical Workloads 377\u003c\/p\u003e \u003cp\u003eImplement a Partition Strategy for Streaming Workloads 378\u003c\/p\u003e \u003cp\u003eImplement a Partition Strategy for Azure Synapse Analytics 378\u003c\/p\u003e \u003cp\u003eDesign and Implement the Data Exploration Layer 379\u003c\/p\u003e \u003cp\u003eDeliver Data in a Relational Star Schema 379\u003c\/p\u003e \u003cp\u003eDeliver Data in Parquet Files 385\u003c\/p\u003e \u003cp\u003eMaintain Metadata 386\u003c\/p\u003e \u003cp\u003eImplement a Dimensional Hierarchy 386\u003c\/p\u003e \u003cp\u003eCreate and Execute Queries by Using a Compute Solution That Leverages SQL Serverless and Spark Cluster 388\u003c\/p\u003e \u003cp\u003eRecommend Azure Synapse Analytics Database Templates 389\u003c\/p\u003e \u003cp\u003eImplement Azure Synapse Analytics Database Templates 389\u003c\/p\u003e \u003cp\u003eAdditional Data Storage Topics 390\u003c\/p\u003e \u003cp\u003eStoring Raw Data in Azure Databricks for Transformation 390\u003c\/p\u003e \u003cp\u003eStoring Data Using Azure HDInsight 392\u003c\/p\u003e \u003cp\u003eStoring Prepared, Trained, and Modeled Data 393\u003c\/p\u003e \u003cp\u003eSummary 394\u003c\/p\u003e \u003cp\u003eExam Essentials 395\u003c\/p\u003e \u003cp\u003eReview Questions 396\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Develop Data Processing 399\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Transform, Manage, and Prepare Data 401\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Ingest and Transform Data 402\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTransform Data Using Azure Synapse Pipelines 404\u003c\/p\u003e \u003cp\u003eTransform Data Using Azure Data Factory 410\u003c\/p\u003e \u003cp\u003eTransform Data Using Apache Spark 414\u003c\/p\u003e \u003cp\u003eTransform Data Using Transact- SQL 429\u003c\/p\u003e \u003cp\u003eTransform Data Using Stream Analytics 431\u003c\/p\u003e \u003cp\u003eCleanse Data 433\u003c\/p\u003e \u003cp\u003eSplit Data 435\u003c\/p\u003e \u003cp\u003eShred JSON 439\u003c\/p\u003e \u003cp\u003eEncode and Decode Data 445\u003c\/p\u003e \u003cp\u003eConfigure Error Handling for the Transformation 450\u003c\/p\u003e \u003cp\u003eNormalize and Denormalize Values 451\u003c\/p\u003e \u003cp\u003eTransform Data by Using Scala 461\u003c\/p\u003e \u003cp\u003ePerform Exploratory Data Analysis 463\u003c\/p\u003e \u003cp\u003eTransformation and Data Management Concepts 473\u003c\/p\u003e \u003cp\u003eTransformation 473\u003c\/p\u003e \u003cp\u003eData Management 480\u003c\/p\u003e \u003cp\u003eAzure Databricks 481\u003c\/p\u003e \u003cp\u003eData Modeling and Usage 485\u003c\/p\u003e \u003cp\u003eData Modeling with Machine Learning 486\u003c\/p\u003e \u003cp\u003eUsage 494\u003c\/p\u003e \u003cp\u003eSummary 500\u003c\/p\u003e \u003cp\u003eExam Essentials 500\u003c\/p\u003e \u003cp\u003eReview Questions 502\u003c\/p\u003e \u003cp\u003eCreate and Manage Batch Processing and Pipelines 505\u003c\/p\u003e \u003cp\u003eDesign and Develop a Batch Processing Solution 507\u003c\/p\u003e \u003cp\u003eDesign a Batch Processing Solution 510\u003c\/p\u003e \u003cp\u003eDevelop Batch Processing Solutions 512\u003c\/p\u003e \u003cp\u003eCreate Data Pipelines 538\u003c\/p\u003e \u003cp\u003eHandle Duplicate Data 560\u003c\/p\u003e \u003cp\u003eHandle Missing Data 569\u003c\/p\u003e \u003cp\u003eHandle Late- Arriving Data 571\u003c\/p\u003e \u003cp\u003eUpsert Data 572\u003c\/p\u003e \u003cp\u003eConfigure the Batch Size 578\u003c\/p\u003e \u003cp\u003eConfigure Batch Retention 581\u003c\/p\u003e \u003cp\u003eDesign and Develop Slowly Changing Dimensions 582\u003c\/p\u003e \u003cp\u003eDesign and Implement Incremental Data Loads 583\u003c\/p\u003e \u003cp\u003eIntegrate Jupyter\/IPython Notebooks into a Data Pipeline 590\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Revert Data to a Previous State 591\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHandle Security and Compliance Requirements 592\u003c\/p\u003e \u003cp\u003eDesign and Create Tests for Data Pipelines 593\u003c\/p\u003e \u003cp\u003eScale Resources 593\u003c\/p\u003e \u003cp\u003eDesign and Configure Exception Handling 593\u003c\/p\u003e \u003cp\u003eDebug Spark Jobs Using the Spark UI 594\u003c\/p\u003e \u003cp\u003eImplement Azure Synapse Link and Query the Replicated Data 594\u003c\/p\u003e \u003cp\u003eUse PolyBase to Load Data to a SQL Pool 595\u003c\/p\u003e \u003cp\u003eRead from and Write to a Delta Table 595\u003c\/p\u003e \u003cp\u003eManage Batches and Pipelines 596\u003c\/p\u003e \u003cp\u003eTrigger Batches 597\u003c\/p\u003e \u003cp\u003eSchedule Data Pipelines 597\u003c\/p\u003e \u003cp\u003eValidate Batch Loads 598\u003c\/p\u003e \u003cp\u003eImplement Version Control for Pipeline Artifacts 604\u003c\/p\u003e \u003cp\u003eManage Data Pipelines 607\u003c\/p\u003e \u003cp\u003eManage Spark Jobs in a Pipeline 609\u003c\/p\u003e \u003cp\u003eHandle Failed Batch Loads 610\u003c\/p\u003e \u003cp\u003eSummary 610\u003c\/p\u003e \u003cp\u003eExam Essentials 611\u003c\/p\u003e \u003cp\u003eReview Questions 612\u003c\/p\u003e \u003cp\u003eDesign and Implement a Data Stream Processing Solution 615\u003c\/p\u003e \u003cp\u003eDevelop a Stream Processing Solution 617\u003c\/p\u003e \u003cp\u003eDesign a Stream Processing Solution 618\u003c\/p\u003e \u003cp\u003eCreate a Stream Processing Solution 630\u003c\/p\u003e \u003cp\u003eProcess Time Series Data 657\u003c\/p\u003e \u003cp\u003eDesign and Create Windowed Aggregates 658\u003c\/p\u003e \u003cp\u003eProcess Data Within One Partition 661\u003c\/p\u003e \u003cp\u003eProcess Data Across Partitions 663\u003c\/p\u003e \u003cp\u003eUpsert Data 665\u003c\/p\u003e \u003cp\u003eHandle Schema Drift 674\u003c\/p\u003e \u003cp\u003eConfigure Checkpoints\/Watermarking During Processing 680\u003c\/p\u003e \u003cp\u003eReplay Archived Stream Data 685\u003c\/p\u003e \u003cp\u003eDesign and Create Tests for Data Pipelines 688\u003c\/p\u003e \u003cp\u003eMonitor for Performance and Functional Regressions 689\u003c\/p\u003e \u003cp\u003eOptimize Pipelines for Analytical or Transactional Purposes 689\u003c\/p\u003e \u003cp\u003eScale Resources 690\u003c\/p\u003e \u003cp\u003eDesign and Configure Exception Handling 691\u003c\/p\u003e \u003cp\u003eHandle Interruptions 694\u003c\/p\u003e \u003cp\u003eIngest and Transform Data 694\u003c\/p\u003e \u003cp\u003eTransform Data Using Azure Stream Analytics 694\u003c\/p\u003e \u003cp\u003eMonitor Data Storage and Data Processing 695\u003c\/p\u003e \u003cp\u003eMonitor Stream Processing 695\u003c\/p\u003e \u003cp\u003eSummary 695\u003c\/p\u003e \u003cp\u003eExam Essentials 696\u003c\/p\u003e \u003cp\u003eReview Questions 697\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Secure, Monitor, and Optimize Data Storage and Data Processing 699\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Keeping Data Safe and Secure 701\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDesign Security for Data Policies and Standards 702\u003c\/p\u003e \u003cp\u003eDesign a Data Auditing Strategy 711\u003c\/p\u003e \u003cp\u003eDesign a Data Retention Policy 716\u003c\/p\u003e \u003cp\u003eDesign for Data Privacy 717\u003c\/p\u003e \u003cp\u003eDesign to Purge Data Based on Business Requirements 719\u003c\/p\u003e \u003cp\u003eDesign Data Encryption for Data at Rest and in Transit 719\u003c\/p\u003e \u003cp\u003eDesign Row- Level and Column- Level Security 722\u003c\/p\u003e \u003cp\u003eDesign a Data Masking Strategy 723\u003c\/p\u003e \u003cp\u003eDesign Access Control for Azure Data Lake Storage Gen 2 724\u003c\/p\u003e \u003cp\u003eImplement Data Security 730\u003c\/p\u003e \u003cp\u003eImplement a Data Auditing Strategy 731\u003c\/p\u003e \u003cp\u003eManage Sensitive Information 739\u003c\/p\u003e \u003cp\u003eImplement a Data Retention Policy 745\u003c\/p\u003e \u003cp\u003eEncrypt Data at Rest and in Motion 748\u003c\/p\u003e \u003cp\u003eImplement Row- Level and Column- Level Security 749\u003c\/p\u003e \u003cp\u003eImplement Data Masking 753\u003c\/p\u003e \u003cp\u003eManage Identities, Keys, and Secrets Across Different Data Platform Technologies 755\u003c\/p\u003e \u003cp\u003eImplement Access Control for Azure Data Lake Storage Gen 2 765\u003c\/p\u003e \u003cp\u003eImplement Secure Endpoints (Private and Public) 772\u003c\/p\u003e \u003cp\u003eImplement Resource Tokens in Azure Databricks 778\u003c\/p\u003e \u003cp\u003eLoad a DataFrame with Sensitive Information 779\u003c\/p\u003e \u003cp\u003eWrite Encrypted Data to Tables or Parquet Files 780\u003c\/p\u003e \u003cp\u003eDevelop a Batch Processing Solution 781\u003c\/p\u003e \u003cp\u003eHandle Security and Compliance Requirements 782\u003c\/p\u003e \u003cp\u003eDesign and Implement the Data Exploration Layer 784\u003c\/p\u003e \u003cp\u003eBrowse and Search Metadata in Microsoft Purview Data Catalog 784\u003c\/p\u003e \u003cp\u003ePush New or Updated Data Lineage to Microsoft Purview 785\u003c\/p\u003e \u003cp\u003eSummary 786\u003c\/p\u003e \u003cp\u003eExam Essentials 787\u003c\/p\u003e \u003cp\u003eReview Questions 789\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Monitoring Azure Data Storage and Processing 791\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMonitoring Data Storage and Data Processing 793\u003c\/p\u003e \u003cp\u003eImplement Logging Used by Azure Monitor 793\u003c\/p\u003e \u003cp\u003eConfigure Monitoring Services 799\u003c\/p\u003e \u003cp\u003eUnderstand Custom Logging Options 821\u003c\/p\u003e \u003cp\u003eMeasure Query Performance 822\u003c\/p\u003e \u003cp\u003eMonitor Data Pipeline Performance 823\u003c\/p\u003e \u003cp\u003eMonitor Cluster Performance 824\u003c\/p\u003e \u003cp\u003eMeasure Performance of Data Movement 824\u003c\/p\u003e \u003cp\u003eInterpret Azure Monitor Metrics and Logs 825\u003c\/p\u003e \u003cp\u003eMonitor and Update Statistics about Data Across a System 828\u003c\/p\u003e \u003cp\u003eSchedule and Monitor Pipeline Tests 830\u003c\/p\u003e \u003cp\u003eInterpret a Spark Directed Acyclic Graph 830\u003c\/p\u003e \u003cp\u003eMonitor Stream Processing 832\u003c\/p\u003e \u003cp\u003eImplement a Pipeline Alert Strategy 832\u003c\/p\u003e \u003cp\u003eDevelop a Batch Processing Solution 832\u003c\/p\u003e \u003cp\u003eDesign and Create Tests for Data Pipelines 832\u003c\/p\u003e \u003cp\u003eDevelop a Stream Processing Solution 837\u003c\/p\u003e \u003cp\u003eMonitor for Performance and Functional Regressions 837\u003c\/p\u003e \u003cp\u003eDesign and Create Tests for Data Pipelines 838\u003c\/p\u003e \u003cp\u003eAzure Monitoring Overview 841\u003c\/p\u003e \u003cp\u003eAzure Batch 841\u003c\/p\u003e \u003cp\u003eAzure Key Vault 842\u003c\/p\u003e \u003cp\u003eAzure SQL 843\u003c\/p\u003e \u003cp\u003eSummary 844\u003c\/p\u003e \u003cp\u003eExam Essentials 844\u003c\/p\u003e \u003cp\u003eReview Questions 846\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Troubleshoot Data Storage Processing 849\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eOptimize and Troubleshoot Data Storage and Data Processing 851\u003c\/p\u003e \u003cp\u003eOptimize Resource Management 854\u003c\/p\u003e \u003cp\u003eCompact Small Files 857\u003c\/p\u003e \u003cp\u003eHandle Skew in Data 859\u003c\/p\u003e \u003cp\u003eHandle Data Spill 860\u003c\/p\u003e \u003cp\u003eFind Shuffling in a Pipeline 862\u003c\/p\u003e \u003cp\u003eTune Shuffle Partitions 864\u003c\/p\u003e \u003cp\u003eTune Queries by Using Indexers 869\u003c\/p\u003e \u003cp\u003eTune Queries by Using Cache 876\u003c\/p\u003e \u003cp\u003eOptimize Pipelines for Analytical or Transactional Purposes 877\u003c\/p\u003e \u003cp\u003eOptimize Pipeline for Descriptive versus Analytical Workloads 886\u003c\/p\u003e \u003cp\u003eTroubleshoot a Failed Spark Job 888\u003c\/p\u003e \u003cp\u003eTroubleshoot a Failed Pipeline Run 890\u003c\/p\u003e \u003cp\u003eRewrite User- Defined Functions 899\u003c\/p\u003e \u003cp\u003eDesign and Develop a Batch Processing Solution 901\u003c\/p\u003e \u003cp\u003eDesign and Configure Exception Handling 902\u003c\/p\u003e \u003cp\u003eDebug Spark Jobs by Using the Spark UI 902\u003c\/p\u003e \u003cp\u003eScale Resources 902\u003c\/p\u003e \u003cp\u003eMonitor Batches and Pipelines 904\u003c\/p\u003e \u003cp\u003eHandle Failed Batch Loads 904\u003c\/p\u003e \u003cp\u003eDesign and Develop a Stream Processing Solution 905\u003c\/p\u003e \u003cp\u003eOptimize Pipelines for Analytical or Transactional Purposes 905\u003c\/p\u003e \u003cp\u003eHandle Interruptions 906\u003c\/p\u003e \u003cp\u003eScale Resources 908\u003c\/p\u003e \u003cp\u003eSummary 909\u003c\/p\u003e \u003cp\u003eExam Essentials 910\u003c\/p\u003e \u003cp\u003eReview Questions 912\u003c\/p\u003e \u003cp\u003eAppendix Answers to Review Questions 915\u003c\/p\u003e \u003cp\u003eChapter 1: Gaining the Azure Data Engineer Associate Certification 916\u003c\/p\u003e \u003cp\u003eChapter 2: CREATE DATABASE dbName; GO 916\u003c\/p\u003e \u003cp\u003eChapter 3: Data Sources and Ingestion 917\u003c\/p\u003e \u003cp\u003eChapter 4: The Storage of Data 918\u003c\/p\u003e \u003cp\u003eChapter 5: Transform, Manage, and Prepare Data 918\u003c\/p\u003e \u003cp\u003eChapter 6. Create and Manage Batch Processing and Pipelines 919\u003c\/p\u003e \u003cp\u003eChapter 7: Design and Implement a Data Stream Processing Solution 920\u003c\/p\u003e \u003cp\u003eChapter 8: Keeping Data Safe and Secure 921\u003c\/p\u003e \u003cp\u003eChapter 9: Monitoring Azure Data Storage and Processing 921\u003c\/p\u003e \u003cp\u003eChapter 10: Troubleshoot Data Storage Processing 922\u003cbr\u003e\u003cbr\u003e Index 925\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Education [\u003ca title=\"See our other books on Education\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Education%20%5BJN%5D%22\"\u003eJN\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Sybex","offers":[{"title":"Brand New","offer_id":52474949337368,"sku":"9781119885429","price":46.48,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781119885429.jpg?v=1785801695","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/mca-microsoft-certified-associate-azure-data-engineer-study-guide-exam-dp-203-paperback-softback-9781119885429","provider":"Freshly Printed Books","version":"1.0","type":"link"}