Microsoft Azure Data Fundamentals will validate your foundational knowledge of core data concepts and how they’re implemented using Azure data services. It also provides a foundation as you prepare for other Azure role-based certifications, like Azure Database Administrator Associate, Azure Data Engineer Associate, and Data Analyst Associate.
This learning path is designed to help you prepare for the DP-900 Microsoft Azure Data Fundamentals exam. Even if you don't plan to take the exam, these courses and hands-on labs will help you gain a solid understanding of Azure's data processing services
Course content
Describe core data concepts
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
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 database servicesfamily 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
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
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
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Course Prerequisites
- General technical knowledge would be helpful
- A free or paid subscription to Microsoft Azure
Who can attend
- Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.
- Candidates beginning to work with data in the cloud.
- Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.
- Senior technical people with exposure to Azure
Number of Hours: 30hrs
Certification
DP-900Key features
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
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