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Microsoft DP-900 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Describe core data concepts (15-20%) | |
| Describe types of core data workloads | - describe batch data - describe streaming data - describe the difference between batch and streaming data - describe the characteristics of relational data |
| Describe data analytics core concepts | - describe data visualization (e.g., visualization, reporting, business intelligence (BI)) - describe basic chart types such as bar charts and pie charts - describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive) - describe ELT and ETL processing - describe the concepts of data processing |
Describe how to work with relational data on Azure (25-30%) | |
| Describe relational data workloads | - identify the right data offering for a relational workload - describe relational data structures (e.g., tables, index, views) |
| Describe relational Azure data services | - describe and compare PaaS, IaaS, and SaaS solutions - describe Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines - describe Azure Synapse Analytics - describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL |
| Identify basic management tasks for relational data | - describe provisioning and deployment of relational data services - describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI) - identify data security components (e.g., firewall, authentication) - identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) - identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.) |
| Describe query techniques for data using SQL language | - compare Data Definition Language (DDL) versus Data Manipulation Language (DML) - query relational data in Azure SQL Database, Azure Database for PostgreSQL, and Azure Database for MySQL |
Describe how to work with non-relational data on Azure (25-30%) | |
| Describe non-relational data workloads | - describe the characteristics of non-relational data - describe the types of non-relational and NoSQL data - recommend the correct data store - determine when to use non-relational data |
| Describe non-relational data offerings on Azure | - identify Azure data services for non-relational workloads - describe Azure Cosmos DB APIs - describe Azure Table storage - describe Azure Blob storage - describe Azure File storage |
| Identify basic management tasks for non-relational data | - describe provisioning and deployment of non-relational data services - describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI) - identify data security components (e.g., firewall, authentication, encryption) - identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) - identify management tools for non-relational data |
Describe an analytics workload on Azure (25-30%) | |
| Describe analytics workloads | - describe transactional workloads - describe the difference between a transactional and an analytics workload - describe the difference between batch and real time - describe data warehousing workloads - determine when a data warehouse solution is needed |
| Describe the components of a modern data warehouse | - describe Azure data services for modern data warehousing such as Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight - describe modern data warehousing architecture and workload |
| Describe data ingestion and processing on Azure | - describe common practices for data loading - describe the components of Azure Data Factory (e.g., pipeline, activities, etc.) - describe data processing options (e.g., Azure HDInsight, Azure Databricks, Azure Synapse Analytics, Azure Data Factory) |
| Describe data visualization in Microsoft Power BI | - describe the role of paginated reporting - describe the role of interactive reports - describe the role of dashboards - describe the workflow in Power BI |
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
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What should you know about the Microsoft DP-900 exam?
The Microsoft DP-900 exam is 60 minutes long and consists of 40-60 questions of various types. Some of these formats may include multiple choice, active screen, drag and drop, build list, best answer, short answer, and case studies, among others. The candidates can find the examples of these question types on the official website. This certification test is designed to evaluate the competence of the professionals in using non-relational and relational data on Azure, as well as the analytics workload that is available on Azure. The exam fee is $99 and the applicants must pay it before registering for and scheduling their test. To complete this exam on the first try, they must achieve at least 720 points on a scale of 100-1000. The languages available for this test include English, German, Korean, Spanish, French, Japanese, and Simplified Chinese.
Microsoft DP-900日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe an analytics workload on Azure | 25-30% | - Describe Azure data analytics services
|
| Describe core data concepts | 25-30% | - Describe ways to represent data
|
| Identify considerations for relational data on Azure | 20-25% | - Describe relational concepts
|
| Describe considerations for working with non-relational data on Azure | 15-20% | - Describe non-relational Azure data services
|
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