Direct from Microsoft, this Exam Ref is the official study guide for the new Microsoft DP-200 Implementing an Azure Data Solution certification exam.
Exam Ref DP-200 Implementing an Azure Data Solution offers professional-level preparation that helps candidates maximize their exam performance and sharpen their skills on the job. It focuses on specific areas of expertise modern IT professionals need to demonstrate real-world mastery of data solution provisioning, data ingestion and transformation, security, data governance, and performance monitoring. Coverage includes:
- Understanding Azure data solutions: data storage and data processing concepts
- Implementing Azure data storage solutions: implementing non-relational and relational data stores, and managing data security
- Managing and developing data processing for Azure data solutions: developing batch processing and streaming solutions
- Monitoring and optimizing Azure data solutions: monitoring data storage and data processing; troubleshooting data partitioning bottlenecks; optimizing Data Lake Storage, Stream Analytics, and Azure Synapse Analytics; and managing the data lifecycle
Microsoft Exam Ref publications stand apart from third-party study guides because they:
- Provide guidance from Microsoft, the creator of Microsoft certification exams
- Target IT professional-level exam candidates with content focused on their needs, not “one-size-fits-all” content
- Streamline study by organizing material according to the exam’s objective domain (OD), covering one functional group and its objectives in each chapter
- Offer concise overviews of every skill covered by the exam
- Feature “Thought Experiments” and “Thought Experiment Answers” to guide candidates through a set of “what if?” scenarios, and prepare them more effectively for Pro-level style exam questions
- Explore big picture thinking around the planning and design aspects of the IT pro’s job role
- Deliver exam tips, summaries, and inline questions and answers to help you identify key points
- Include “Need more review?” reader aids pointing to additional study materials when readers need them
For more information on Exam DP-200 and the Microsoft Certified: Azure Data Engineer credential, visit https://docs.microsoft.com/en-us/learn/certifications/azure-data-engineer
Direct from Microsoft, this Exam Ref is the official study guide for the new Microsoft DP-200 Implementing an Azure Data Solution certification exam.
Exam Ref DP-200 Implementing an Azure Data Solution offers professional-level preparation that helps candidates maximize their exam performance and sharpen their skills on the job. It focuses on specific areas of expertise modern IT professionals need to demonstrate real-world mastery of data solution provisioning, data ingestion and transformation, security, data governance, and performance monitoring.
| Acknowledgments |
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vi | |
| About the Authors |
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vii | |
| Introduction |
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ix | |
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Chapter 1 Understand Azure data solutions |
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1 | (32) |
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2 | (16) |
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2 | (2) |
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4 | (4) |
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8 | (10) |
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18 | (8) |
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19 | (1) |
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19 | (1) |
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Lambda and kappa architectures |
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20 | (2) |
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Azure technologies used for data processing |
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22 | (4) |
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26 | (3) |
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26 | (1) |
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Hybrid ETL with existing on-premises SSIS and Azure Data Factory |
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26 | (2) |
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Internet of things architecture |
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28 | (1) |
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29 | (2) |
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31 | (1) |
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31 | (2) |
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Chapter 2 Implement data-storage solutions |
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33 | (82) |
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Implement non-relational data stores |
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33 | (55) |
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Implement a solution that uses Cosmos DB, Azure Data Lake Storage Gen2, or Blob storage |
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34 | (12) |
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46 | (2) |
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Implement a consistency model in Cosmos DB |
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48 | (2) |
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Provision a non-relational data store |
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50 | (20) |
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Provision an Azure Synapse Analytics workspace |
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70 | (4) |
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Provide access to data to meet security requirements |
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74 | (8) |
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Implement for high availability, disaster recovery, and global distribution |
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82 | (6) |
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Implement relational data stores |
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88 | (16) |
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Provide access to data to meet security requirements |
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88 | (9) |
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Implement for high availability and disaster recovery |
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97 | (2) |
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Implement data distribution and partitions for Azure Synapse Analytics |
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99 | (3) |
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102 | (2) |
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104 | (6) |
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Implement dynamic data masking |
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104 | (3) |
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Encrypt data at rest and in motion |
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107 | (3) |
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110 | (1) |
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111 | (3) |
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114 | (1) |
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Chapter 3 Manage and develop data processing for Azure Data Solutions |
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115 | (104) |
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116 | (73) |
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Develop batch-processing solutions using Azure Data Factory and Azure Databricks |
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119 | (17) |
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Implement the Integration Runtime for Azure Data Factory |
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136 | (6) |
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Create pipelines, activities, linked services, and datasets |
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142 | (15) |
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Create and schedule triggers |
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157 | (5) |
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Implement Azure Databricks clusters, notebooks, jobs, and autoscaling |
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162 | (6) |
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Ingest data into Azure Databricks |
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168 | (8) |
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Ingest and process data using Azure Synapse Analytics |
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176 | (13) |
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189 | (24) |
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Stream-transport and processing engines |
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191 | (1) |
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Implement event processing using Stream Analytics |
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192 | (3) |
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Configure input and output |
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195 | (6) |
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Select the appropriate built-in functions |
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201 | (12) |
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213 | (3) |
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216 | (2) |
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218 | (1) |
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Chapter 4 Monitor and optimize data solutions |
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219 | (62) |
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220 | (24) |
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Monitor an Azure SQL Database |
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220 | (5) |
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Monitor Azure SQL Database using DMV |
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225 | (1) |
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226 | (3) |
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Implement Azure Data Lake Storage monitoring |
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229 | (1) |
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Implement Azure Synapse Analytics monitoring |
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229 | (2) |
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Implement Cosmos DB monitoring |
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231 | (1) |
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Configure Azure Monitor alerts |
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232 | (4) |
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Audit with Azure Log Analytics |
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236 | (8) |
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244 | (16) |
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Monitor Azure Data Factory pipelines |
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244 | (3) |
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247 | (2) |
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Monitor Azure Stream Analytics |
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249 | (1) |
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Monitor Azure Synapse Analytics |
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250 | (5) |
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Configure Azure Monitor alerts |
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255 | (1) |
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Audit with Azure Log Analytics |
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256 | (4) |
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Optimize Azure data solutions |
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260 | (16) |
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Troubleshoot data-partitioning bottlenecks |
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260 | (1) |
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Partitioning considerations |
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261 | (2) |
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Partition Azure SQL Database |
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263 | (2) |
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Partition Azure Blob storage |
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265 | (1) |
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266 | (1) |
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Optimize Azure Data Lake Storage Gen2 |
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267 | (1) |
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Optimize Azure Stream Analytics |
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268 | (1) |
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Optimize Azure Synapse Analytics |
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269 | (3) |
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Manage the data life cycle |
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272 | (4) |
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276 | (2) |
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278 | (1) |
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279 | (2) |
| Index |
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281 | |
Daniel A. Seara is an experienced software developer. He has more than 20 years as a technical instructor, developer, and development consultant. Daniel has worked as a software consultant in a wide range of companies in Argentina, Spain, and Peru. He has been asked by Peruvian Microsoft Consulting Services to help several companies in their migration path to .NET development. Daniel was Argentina's Microsoft regional director for four years and was the first nominated global regional director, a position he held for two years. He also was the manager of the Desarrollador Cinco Estrellas I (Five Star Developer) program, one of the most successful training projects in Latin America. Daniel held Visual Basic MVP status for more than 10 years, as well as SharePoint Server MVP status from 2008 until 2014. Additionally, Daniel is the founder and dean of Universidad. NET, the most-visited Spanish-language site to learn .NET. In 2005, he joined Lucient, the leading global company on the Microsoft Data Platform, where he has been working as a trainer, consultant, and mentor.
Francesco Milano has been working with Microsoft technologies since 2000. Francesco specializes in the .NET Framework and SQL Server platform, and he focuses primarily on back-end development, integration solutions, and relational model design and implementation. He is a regular speaker at top Italian data platform conferences and workshops. Since 2013, Francesco has also explored emerging trends and technologies pertaining to big data and advanced analytics, consolidating his knowledge of products like HDInsight, Databricks, Azure Data Factory, and Azure Synapse Analytics. In 2015, Francesco joined Lucient, the leading global company on the Microsoft Data Platform, where he has been working as a trainer, consultant, and mentor.
Danilo Dominici is an independent consultant, trainer, and speaker, with more than 20 years of experience with relational databases and software development in both Windows and *nix environments. He has specialized in SQL Server since 1997, helping customers design, implement, migrate, tune, optimize, and build HA/DR solutions for their SQL Server environments. Danilo has been a Microsoft Certified Trainer since 2000. He works as a trainer for the largest Microsoft learning partners in Italy, teaching SQL Server and Windows server courses. He is also a regular contributor and speaker at community events in Italy and is the co-leader of PASS Global Italian Virtual Chapter, the Italian-speaking virtual group. For his commitment, Microsoft has recognized Danilo as a Data Platform MVP since 2014. Danilo was a SQL Server and PostgreSQL DBA and a VMWare administrator in Regione Marche, a local government organization in Italy, from 2004 to 2017. Later he became a DBA and a web developer within the Polytechnic University of Marche. Danilo has been part of Lucient since 2011.
