Overview

PASSING the DP-900: Azure Data Fundamentals examination will demonstrate your subject matter expertise to your current and future employers. Azure is one the most popular and widely used commercial clouds in the world, and data is becoming a businesses most valuable asset. Understanding the core Azure data services, storage mechanisms, security suite, and core technologies will separate your resume from the rest. This certification can potentially land you a high-paying job in the cloud & tech industry. The cloud is the future, and your career growth and earning potential starts here with DP-900: Azure Data Fundamentals. Our Azure Data Fundamentals practice test questions are based off the official DP-900: Azure Data Fundamentals Study Guide, and various associated azure data services documentations available online. Additionally, our questions were verified and validated by certified Azure cloud engineers. And to make it even better, we provided detailed explanations to each question, so you can truly master the concepts, understand why the answer is correct, and most importantly, why the other answer choices are wrong. We designed our practice tests to mimic the real exam. Our questions are asked the exact same way as the real exam, and they come with detailed explanations, diagrams, and valuable reference links to help you learn. Our practice tests will be the final step of your preparation. Please trust us, we spent hours curating these questions. We will be with you every step of the way. Our only question is this - are you ready? Let's get you certified right now.The DP-900: Azure Data Fundamentals examination will test you on these key skills: (1.) Describe core data concepts (25-30%)Describe ways to represent dataDescribe features of structured dataDescribe features of semi-structuredDescribe features of unstructured dataIdentify options for data storageDescribe common formats for data filesDescribe types of databasesDescribe common data workloadsDescribe features of transactional workloadsDescribe features of analytical workloadsIdentify roles and responsibilities for data workloadsDescribe responsibilities for database administratorsDescribe responsibilities for data engineersDescribe responsibilities for data analysts(2.) Identify considerations for relational data on Azure (20-25%)Describe relational conceptsIdentify features of relational dataDescribe normalization and why it is usedIdentify common structured query language (SQL) statementsIdentify common database objectsDescribe relational Azure data servicesDescribe the Azure SQL family of products including Azure SQL Database, Azure SQLManaged Instance, and SQL Server on Azure Virtual MachinesIdentify Azure database services for open-source database systems(3.) Describe considerations for working with non-relational data on Azure (15-20%)Describe capabilities of Azure storageDescribe Azure Blob storageDescribe Azure File storageDescribe Azure Table storageDescribe capabilities and features of Azure Cosmos DBIdentify use cases for Azure Cosmos DBDescribe Azure Cosmos DB APIs(4.) Describe an analytics workload on Azure (25-30%)Describe common elements of large-scale analyticsDescribe considerations for data ingestion and processingDescribe options for analytical data storesDescribe Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Azure HDInsight, and Azure Data FactoryDescribe consideration for real-time data analyticsDescribe the difference between batch and streaming dataDescribe technologies for real-time analytics including Azure Stream Analytics, Azure Synapse Data Explorer, and Spark Structured StreamingDescribe data visualization in Microsoft Power BIIdentify capabilities of Power BIDescribe features of data models in Power BIIdentify appropriate visualizations for data

Skills

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