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    Home»All»How to Become a Microsoft Certified Azure Data Engineer

    How to Become a Microsoft Certified Azure Data Engineer

    Trevor James.cBy Trevor James.cDecember 25, 2021No Comments10 Mins Read
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    Data engineering is among the most sought-after jobs. According to a Dice.com study, the data engineering field saw an increase of 88% in job advertisements for data engineers, which is the highest rate of growth among all tech jobs.

    If you’re interested in data engineering, you’ll have to determine which technologies you want to master because it’s not possible to be an expert in all areas of this broad field. Microsoft has been a leading data technology company for a long time; however, is it still an industry leader? Absolutely. Microsoft has pushed very hard to the cloud through Azure. Azure services. Azure has the second-highest market share of cloud providers and is growing at more than two times the speed of Amazon Web Services.

    In addition, Microsoft is so focused on Azure and its other cloud services that it will end the entire range of certification examinations in the field of Windows Server and SQL Server by June 30, 2020. This is a clear indication that the value of technology on-premises is diminishing.

    So, what exactly does the Azure Data Engineer do? Here’s the information from Microsoft states:

    “Azure Data engineers” are accountable for data-related data implementation tasks, which include providing data storage services as well as ingesting batch and streaming data, processing data, setting up security requirements, setting up retention policies for data as well as identifying performance bottlenecks, and accessing data sources from outside.”

    Are you confident in the idea that Azure Data Engineering is a booming field worth exploring? If so, then you’re ready to jump into Azure training online: Implementing an Azure Data Solution and designing the Azure Data Solution. These two learning paths blend the theories, technical expertise as well as hands-on experience which you’ll need to gain the certification and feel comfortable working in a live-production environment:

    If you’re in need of more convincing, then let’s get into the details of becoming a Microsoft Certified Azure Data Engineer. But before that check this link if you are interested in joining this field as a microsoft security operations analyst.

    The Exams

    To earn this certification for this certification, you must take two tests, namely both DP 200 and DP 201. The DP-200 test focuses on configuration and implementation, while the DP-201 exam is focused on design.

    Exam DP-200

    These are the subjects included in the exam DP-200 and the weights of each of them:

    • Implement data storage solutions (40-45%)
    • Develop and manage processes for data (25-30 25-30%)
    • Optimize and monitor the data solutions (30-35 percent)

    Let’s not get into detail about each and every aspect of the test guide; however, I will review some details of what you’ll need to be aware of.

    The primary and largest part of the exam manual is about the use of solutions for data storage. These solutions are split into relational and non-relational datastores. In the past, Microsoft’s most popular database solution for relational databases included SQL Server. If you were looking to move from on-premises SQL Server to Azure, you could simply execute SQL Server in a virtual machine running on Azure; however, in most instances, you’d be better by using Azure SQL Database instead.

    The benefit is that it’s managed and comes with a lot of built-in functions that enable it to scale easily and also provide an extremely high level of reliability, as well as disaster restoration and worldwide distribution. You must know how to configure each of the features. SQL Database is not exactly identical to SQL Server, but it’s similar enough to have any trouble converting to it. If you truly need SQL Server compatibility, then you can make use of SQL Database Managed Instance.

    Another data storage service that is relational can be found in Azure Synapse Analytics, formerly called Azure SQL Data Warehouse. Based on its name, it’s intended to provide analytics, not transaction processing. It lets you organize and analyze large quantities of data. The most efficient method of importing information into Synapse Analytics is to use Polybase, and it’s crucial to understand how to utilize it. To ensure that you can make the queries as quick and efficient as possible, it is necessary to divide the database into several shards. You must ensure that you use the appropriate distribution technique.

    Security is, of course, essential to SQL Database as well as Synapse Analytics, not just for limiting access to information, but for other reasons such as concealing on credit card numbers or for encrypting all databases.

    That’s for relational databases, But what do you feel about non-relational datastores? These are services that keep unstructured information like videos or documents. The oldest Azure service in this area is Blob storage. This is a very accessible and extremely durable storage space for digital items of any kind. As opposed to filesystems, Blob storage features flat structures. The objects aren’t organized in the form of a system of folders. It’s possible to make it appear like this by clever naming conventions. However, this is really just creating a tree structure.

    For a real hierarchical structure, utilize Azure Data Lake Storage Gen2 that is constructed on top of the Blob storage. It’s particularly helpful for large processing systems such as Azure Databricks.

    The last non-relational datastore that you should be aware of to pass the test can be found in Cosmos DB. It is an impressive database system due to the fact that it is able to grow globally without sacrificing speed or flexibility. It also supports various kinds of data models, including key-value, document, graph broad column. Another interesting aspect is the capability to accommodate five different levels of consistency ranging from the strongest to the ultimate consistency.

    Similar to SQL Database or Synapse Analytics, You need to be aware of the best way to configure security, partitioning higher availability, disaster recovery, along global distribution for Cosmos DB.

    The second section of the exam manual covers the management and development of software for processing data. It is divided into two sections: streams and batch processing. The two major Batch processing solutions comprise Azure Data Factory and Azure Databricks.

    Data Factory makes it easy to transfer data from one store to another, for instance, to Blob storage into SQL Database. Data Factory also makes it simple to convert data into a new format, and something is accomplished using services such as Databricks in the background. It is possible to create sophisticated automated processing pipelines by connecting several transformation processes that are set off with a trigger that responds in response to an incident.

    Azure Databricks is a managed data analytics service. It is based upon Apache Spark, which is an extremely popular open-source analytics and machine-learning framework. It is also possible to use Spark jobs using Azure HDInsight. However, Databricks is the preferred choice which is why it’s the one you’ll need to know best to pass the test. The main Databricks subjects covered include clusters, data ingestion notebooks, jobs, and autoscaling.

    The most significant service for processing streams that is available for stream processing is Azure Stream Analytics. You must know how to import data into this service via other applications and how to process streams of data by using various windowing functions, and then how to send the results to a different service.

    The last section of the exam preparation guide will focus on monitoring and improving data solutions. The primary service to consider for the section in question is Azure Monitor, which is a tool you can use to manage alerts and monitor them for nearly each and every Azure service. One of the most important features in Azure Monitor is called Log Analytics that is a tool you can use to set up auditing.

    The section on optimization doesn’t contain new services. Instead, you should be aware of ways to improve the performance of applications like Stream Analytics, SQL Database as well as Synapse Analytics. Utilizing the proper partitioning technique is among the most crucial optimization methods.

    In closing, I’d like to mention that the DP-200 exam is focused on the implementation and configuration of data services; it is essential to understand how to set up data services within the Azure portal. Therefore, the test will have tasks you must complete in the real-world laboratory! If you’re concerned about how you’ll manage to complete the required amount of practice with hands-on practice, refer to the preparation for Exams part below.

    Exam DP-201

    The following are the topics that are included in the exam DP-201 and the importance of each one:

    • Design Azure data storage solutions (40-45%)
    • Design data processing solutions (25-30%)
    • Design to ensure data security and conformity (25-30 percent)

    While the DP-200 test is about the implementation of the exam, the DP-201 test is focused on design, which means it is more focused on concepts and planning as opposed to getting everything set up.

    The most important and the first part of the exam’s guideline is about creating solutions for data storage. You must know the best Azure services to suggest to satisfy your business needs. Similar to DP-200, These solutions are split into relational datastores, which include Azure SQL Database as well as Azure Synapse Analytics and non-relational data stores like Cosmos Data Lake Storage Gen2, Data Lake Storage Gen2 as well as Blob storage.

    For all the above-mentioned services it is essential to understand how to make:

    • Partitioning and distribution of data
    • High scalability, taking into consideration multiple areas, latencies, as well as throughput
    • Disaster recovery, as well as
    • High availability

    The next part of the exam manual is focused on designing algorithms for data processing. It’s split into stream and batch processing. In order to process batches, it is necessary to be able to create solutions with Azure Data Factory and Azure Databricks. To process streams, you’ll need to be able to create solutions with Stream Analytics and Azure Databricks. As you can see, Azure Databricks is a vital service in data processing as it is used for batch as well as stream processing. It is also important to understand how to access the data of other Azure services and also how to transfer the results to other services.

    The last section of the exam manual concerns Data security as well as compliance. The first step is to understand how to protect your datastores. The most crucial decision to make is the authentication method you choose for different scenarios. In general, it’s preferred to use Azure Active Directory authentication than embedding an access code within your application code. Access control based on role and ACLs (or Access Control Lists) are both essential.

    The second section is designed to create the security of data policies and standards. A few of the subjects include:

    • Encryption like Transparent Data Encryption
    • Data auditing
    • Data masking, like hiding credit card numbers
    • Data privacy and classification
    • Data retention
    • Archiving and
    • Purging

    Studying for the Exams

    Even if you have plenty of knowledge of Azure Data Services, I would suggest that you invest a substantial amount in studying the tests since DP-200 and DP-201 will test you thoroughly for your skills and knowledge.

    Best of luck with the tests!

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