How difficult is the Microsoft Azure DP900 Exam? Blog

You want to learn core data concepts? You are interested in understanding the concepts of relational and unrelational data, as well as different data workloads. You must be familiar with the concepts of Microsoft Azure DP900 certification. It is essential that you have the right certifications to validate your skills and abilities as you seek a new career. These credentials allow employers to get to know you better, and to see the value you bring to the organization.
Microsoft is a well-known company in the IT industry. Its certifications are widely recognized. You should be curious about the process of earning the Microsoft Azure DP-900 certificate and the benefits it offers in job searching. Here’s a blog post with all the details and possible resources to help you prepare for the exam.
Microsoft Azure DP-900 Exam Format
The Microsoft Azure Data Platform DP900 certification exam verifies candidates’ solid knowledge of the basic data concepts required to create scalable, reliable cloud applications using Microsoft Azure. Candidates must be able to distinguish between relational and unrelational data as well as the various types of database systems.
DP-900 Exam Details
NameMicrosoft Azure FundamentalsExam CodeAZ-900Duration85 minsExam FormatMultiple Choice and Multi-Response QuestionsExam TypeCloud ComputingNumber of Questions40-60 QuestionsEligibility/Pre-RequisiteNILTotal Exam Fee$99 USDExam LanguageEnglish, Spanish, German, Chinese (Simplified), French, Korean, JapanesePass Score700 (on a scale of 1-1000)DP-900 Exam Topics
The course outline can be used to help you understand the themes of the exam and provide a breakdown of key content information for future candidates who want to become certified.
The Microsoft Azure DP-900 covers these topics:
Microsoft DP-900 Exam updated in the course outline as of April 23, 2021.
The Microsoft DP-900 exam topics have been updated.
Topic 1: Describe core data concepts (15-20%)
1.1 Description of types core data workloads
describing batch data
explaining streaming data
The difference between streaming and batch data
Describe the characteristics of relational data
1.2 Data analytics core concepts
Describe data visualization (e.g. visualization, reporting, business intelligence).
The basic chart types, such as pie charts and bar charts, are described below
Describe analytics techniques (e.g. predictive, predictive, predictive, cognitive, and descriptive)
ELT and ETL processing described
Describe the concepts of data processing
Topic 2: How to work with Azure relational data (25-30%)
2.1 Describe relational data workloads
Identifying the right data to support a relational workload
Describe relational data structures (e.g. tables, index, views).
2.2 Describe relational Azure data services
Compare and describe PaaS, IaaS and SaaS delivery models
The Azure SQL family of products includes Azure SQL Database, Azure SQL Managed Instance and SQL Server on Azure Virtual machines.
explaining Azure Synapse Analytics
This article describes Azure Database For PostgreSQL, Azure Database For MariaDB, and Azure Database For MySQL
2.3 Identify basic management tasks related to relational data
This article describes provisioning and deployment relational data services
This article describes a method of deployment that includes ARM templates and Azure Portal.
Recognizing the basics of connectivity issues, such as accessing from on premises, access with Azure VNets and access from the Internet, authentication, firewalls
Identifying the query tools (e.g. SQL Server Management Studio and Azure Data Studio),
2.4 SQL language query techniques: Describe query techniques
Compare DDL versus DML
PostgreSQL, MySQL and Azure SQL Database allow you to query relational data
Topic 3: How to work with Azure non-relational data (25-30%)
3.1 Describe non-relational data loads
Describe the characteristics of non-relational information
Describe the types of NoSQL and non-relational data
Recommend the correct datastore
When to use non-relational information
3.2 Describe non-relational data offers on Azure
Find Azure data services to support non-relational workloads
describe Azure Cosmos DB APIs
describing Azure Table storage
describe Azure Blob storage
describing Azure File storage
3.3 Identify the basic management tasks for non-relational information
This article describes provisioning and deployment non-relational data service
This video explains how to deploy ARM templates, Azure Portal and Azure PowerShell. It also demonstrates the Azure command-line interface.
Identify data security components (e.g. firewall, authentication, encryption).
Identifying the basic connectivity issues (e.g. accessing from on-premises or access with Azure VNets, accessing from the Internet, authentication, firewalls).
Identify management tools for non-relational information
Topic 4: Describe an Azure analytics workload (25-30%)
4.1 Describe analytics workloads
Describe transactional workloads
The difference between an analytics and transactional workload
Describe the difference between batching and real-time
Data warehousing workloads described
Determine when a data warehouse solution will be needed
4.2 Describe the components and functions of a modern data warehouse
describing Azure data services for modern data warehousing like Azure Data Lake, Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight
Explaining the modern data warehouse architecture and workload
4.3 Describe data processing and ingestion on Azure
Common practices for data loading
Description of Azure Data Factory components (e.g. pipeline, activities, etc.).
describing data processing options (e.g., HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)
4.4 Descrizione

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