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Preparation Process for Microsoft DP-900 Exam

The learners can use different training options that Microsoft offers to prepare for the DP-900 test. The first step in your preparation process is to go over the exam objectives in detail. They can be found on the official website. The resources to help understand these topics are also available on the vendor’s webpage. Microsoft comes with a paid instructor-led training as well as free learning paths as the best prep options for your certification test.

• Instructor-Led Training

  This is a paid training course that is available in-classroom or as virtual classes. The Microsoft Azure Data Fundamentals course is designed to teach the candidates the fundamentals of the concepts of database in the Cloud environments. The students will be equipped with the basic skills in the domain of Cloud data services. They will also be able to develop foundational knowledge and skills in Cloud data services within Microsoft Azure.

• Practice Test

  The official practice test is also available to help the examinees gain confidence in their test-taking skills. The candidates can use it to evaluate their readiness for the real exam. They can also get familiar with the pattern of the test and develop competence in answering the exam questions. The official practice test can be found on the Microsoft website.

• Online Learning Paths

  This option of learning is free and made up of seven paths with different modules for each. The candidates for this option are those with the ability to study on their own. The self-paced learning paths offer a comprehensive outline and lessons on the topics of the exam.

• Study Guide

  The Exam Ref DP-900: Microsoft Azure Data Fundamentals book is another good resource for preparation. Authored by Daniel A. Seara, Francesco Milano, this study guide covers the in-depth analysis of the topics and offers some practical skills that will help you take the test. The book also comes with the sample exam questions to help you ace your test.

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Workload analytics on Azure

• Analytics workloads – under this topic, candidates should learn more about transactional workloads as well as data warehousing workloads. Also, they have to get skilled in differentiating between an analytics and a transactional workload, know the difference between real and batch time, and be able to determining when a data warehouse solution is required.
• Data visualization in Microsoft Power BI – this topic requires candidates to learn more about paginated reporting, dashboards, interactive reports, as well as workflow in Power BI.
• Elements of a modern data warehouse – this sub-section is focused on Azure data services related to modern data warehousing. In addition, applicants should be familiar with modern data warehousing workload and architecture.
• Date processing and ingestion on Azure – main topics within this subdomain include data loading common practices, Azure Data Factory components (activities, pipeline, etc.), and data processing.

Explain the Techniques Involved in Working with Non-Relational Data on Microsoft Azure: 25-30%

• Identify the Fundamental Management Functions for Non-Relational Data: The examinees should have competence in explaining deployment and provisioning of non-relational data and the techniques for deployment. They also need the skills in identifying the components of data security, fundamental connectivity issues, and non-relational data management tools.
• Explain Non-Relational Data Workloads: The candidates should be able to explain the attributes of non-relational data and types of NoSQL and non-relational data. They need to have expertise in recommending the appropriate data stores and establishing them to utilize non-relational data.
• Explain Offerings of Non-Relational Data on Azure: The individuals need to have competence in explaining Azure Table storage, Azure File storage, Azure data service for non-relational workloads, Azure Blob Storage, and Azure Cosmos DB APIs.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900

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