How to operate with non-relational data on Azure
The main concepts covered in this domain include:
- Non relation data workloads – this sub-section mostly emphasizes the features of non-relational data, when to use it, one's knowledge of the variants of NoSQL and non-relational data, and the ability to choose and recommend appropriate data store.
- Core administration tasks – this sub-domain covers the processes of deployment and provisioning when it comes to non-relational data, data security, diverse tools for management, and defining the issues with connectivity.
- Offerings non-relational data on Azure – within this topic, the learner will be conversant with the following in Azure: data services, Cosmos DB APIs, Table storage, Blob storage, File storage.
Helpful Training Course for Acing DP-900
To help students get fully ready for DP-900, Microsoft has created an official 1-day teacher-guided program for students named ‘Course DP-900T00-A: Microsoft Azure Data Fundamentals’. There are 4 modules in this course which will address all the topics needed for the Microsoft DP-900. However, such a class does not have any related lab exercises, meaning students will not get the scope for applying the things they have learnt in theory. In general, this training is perfect for those who want to learn the main concepts and skills needed to provide cloud data services with the help of Microsoft Azure.
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 |
The Microsoft DP-900 test evaluates the ability of the candidates to execute specific technical tasks. The examinees must understand these areas before they take this test. The topics that this certification exam covers are as follows:
Explain the Concepts of Core Data: 15-20%
- Explain the Core Concepts of Data Analytics: The candidates need to be able to explain data visualization, analytics techniques, data processing concepts, ETL and ELT processing, as well as the basic types of charts, including pie charts and bar charts.
- Explain Core Data Workloads Types: The test takers should be able to explain batch data, attributes of relational data, streaming data, and the differences between streaming and batch data.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
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