Microsoft
Microsoft Certified: Azure Data Fundamentals
DP-900: Azure Data Fundamentals
Azure Data Fundamentals: Azure Analytics Workloads
Azure Data Fundamentals: Azure Cosmos DB
Azure Data Fundamentals: Azure Data Ingestion & Processing
Azure Data Fundamentals: Azure Data Visualization
Azure Data Fundamentals: Azure SQL Querying Techniques
Azure Data Fundamentals: Data Analytics
Azure Data Fundamentals: Data Workloads
Azure Data Fundamentals: Modern Data Warehousing
Azure Data Fundamentals: Non-relational Data Management
Azure Data Fundamentals: Non-relational Data Services
Azure Data Fundamentals: Non-relational Data Workloads
Azure Data Fundamentals: Provisioning & Configuring Relational Data Services
Azure Data Fundamentals: Relational Data Management
Azure Data Fundamentals: Relational Data Workloads

DP-900 Azure Data Fundamentals: Azure Analytics Workloads

Course Number:
it_clazdataf_11_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Azure Analytics Workloads

  • discover the key concepts covered in this course
  • use Azure Synapse Analytics service
  • applying best practices for Synapse SQL pool
  • describe Data Warehouse Units (DWU)
  • compare transactional and analytic workloads
  • compare batch and real time data processing
  • use Azure Portal to create a Synapse SQL pool
  • use Azure PowerShell to create a Synapse SQL pool
  • describe Data warehousing workloads
  • recognize when to use a data warehouse solution
  • use Azure Data Lake Analytics
  • summarize the key concepts covered in this course

Overview/Description
Azure Synapse Analytics is a limitless analytics service that brings together data warehousing and big data analytics. In this course, you will learn about analytics workloads, including Azure Synapse Analytics, Azure Synapse SQL pool, Data Warehouse Units. You'll also learn about the difference between transactional and analytic workloads and batch and real time data processing. You'll use Azure Portal and Azure PowerShell to create a Synapse SQL pool and Azure Data Lake Analytics. You'll learn about data warehousing workloads and when to use a data warehouse solution. Finally, you'll learn about the different Azure Data Lake Analytics. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Azure Cosmos DB

Course Number:
it_clazdataf_09_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Azure Cosmos DB

  • discover the key concepts covered in this course
  • describe Azure Cosmos DB
  • describe the Azure Cosmos DB resource model
  • provision an Azure Cosmos database
  • configure an Azure Cosmos database
  • use Cosmos DB to query data
  • describe Azure Cosmos DB APIs
  • use Core (SQL) API common commands for Azure Cosmos DB
  • create a database and a collection for MongoDB API using the Azure Cosmos DB
  • create an Azure Cosmos database using the Cassandra API
  • create an Azure Cosmos database using the Azure Table API
  • provision and query an Azure Cosmos database using the Gremlin API
  • summarize the key concepts covered in this course

Overview/Description
Cosmos DB is a fully managed NoSQL database for modern app development. In this course, you'll learn about non-relational data offerings on Azure, including Cosmos DB and the different entities in the resource model. You'll learn how to provision and configure Cosmos DB and query data. Next, you'll explore the various Cosmos DB APIs and learn how to use Core (SQL) API for Cosmos DB. Finally, you'll examine how to use the Cosmos DB API, as well as how to use the Cassandra, Azure Table, and Gremlin APIs in Cosmos DB. This course is one in a series that prepares learners for Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Azure Data Ingestion & Processing

Course Number:
it_clazdataf_13_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Azure Data Ingestion & Processing

  • discover the key concepts covered in this course
  • identify loading strategies for Synapse SQL pools
  • describe Azure data factory pipelines and activities
  • create an Azure data factory
  • use the Azure data factory copy data tool to copy data
  • use Azure Synapse Analytics PolyBase to ingest data
  • use SQL Server Integration Services (SSIS) to ingest data
  • use Azure Databricks to ingest data
  • use Azure Synapse Analytics to load data
  • use Azure Data Lake to load data
  • summarize the key concepts covered in this course

Overview/Description

Data ingestion and processing allows your data to be assessed, used, and analyzed. In this course, you値l learn about Azure data ingestion and processing, including loading strategies for Synapse SQL Pools. You'll examine Azure data factory pipelines and activities, as well as how to create an Azure data factory. Next, you'll learn how to use the data factory copy data tool to copy data. Finally, you'll explore how to use SQL Server Integration Services, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake to ingest data. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.



Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Azure Data Visualization

Course Number:
it_clazdataf_14_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Azure Data Visualization

  • discover the key concepts covered in this course
  • describe Power BI
  • use Power BI to optimize your data
  • use Power BI to load datasets
  • use Power BI to create a dashboard
  • use paginated reporting in Power BI
  • use Power BI to publish reports
  • use interactive reports in Power BI
  • use different types of visualizations in Power BI
  • describe workflows in Power BI
  • recognize security and administration concepts in Power BI
  • summarize the key concepts covered in this course

Overview/Description

Power BI allows you to visualize your data and gain deeper insight by creating interactive and immersive dashboards and reports. In this course, you'll learn how to use Microsoft Power BI to optimize data, load datasets, and create dashboards. Next, you'll explore how to use Power BI for paginated and interactive reports, as well as for publishing reports. You'll also examine how to use the different types of Power BI visualizations. Finally, you'll learn about workflows and Power BI security and administration. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.



Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Azure SQL Querying Techniques

Course Number:
it_clazdataf_06_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Azure SQL Querying Techniques

  • discover the key concepts covered in this course
  • describe the uses, features, and limitations of Structured Query Language (SQL)
  • use Data Definition Language (DDL) in Microsoft SQL Server Management Studio (SSMS)
  • use Data Manipulation Language (DML) in Microsoft SQL Server Management Studio (SSMS)
  • use the Azure portal to query Azure SQL Database
  • use SQL Server Management Studio (SSMS) to query Azure SQL Database
  • use Data Studio to query Azure SQL Database
  • use the sqlcmd utility to query Azure SQL Database
  • use PostgreSQL to query relational data
  • use MySQL to query relational data
  • use MariaDB to query relational data
  • summarize the key concepts covered in this course

Overview/Description
Azure SQL is used for extracting and organizing data that is stored in a relational database. In this course, you'll learn how to recognize and apply data querying techniques using SQL, Data Definition Language, and Data Manipulation Language. You値l start by learning about Structured Query Language including its uses, features, and limitations. You値l examine how to work with the Data Definition Language and Data Manipulation Language. Next, you'll learn how to query Azure SQL Database using the Azure portal, SSMS, Data Studio, and the sqlcmd utility. Finally, you'll discover how to query relational data in PostgreSQL, MySQL, and MariaDB. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Data Analytics

Course Number:
it_clazdataf_02_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Data Analytics

  • discover the key concepts covered in this course
  • describe Azure Data Explorer
  • use Azure Data Explorer for data visualization
  • choose a data analytics technology for reporting
  • describe SQL Server Reporting Services (SSRS)
  • recognize different types of data charts
  • describe analytic techniques
  • describe how stream analytics work
  • identify the different types of stream analytics data
  • identify the different Azure core storage services
  • extract, load, and transform data
  • extract, transform, and load data
  • summarize the key concepts covered in this course

Overview/Description
Data analytics enables you to extract valuable insights from data and uncover patterns. In this course, you'll learn about data analytics core concepts. You'll examine data visualization, including business intelligence and reporting using Azure Data Explorer, a fully-managed big data analytics cloud platform. You'll then learn about SQL Server Reporting Services, data chart types, and different analytic techniques. You'll explore stream analytics and the associated data types. Finally, you'll learn to use extract, load, and transform data processing and also extract, transform, and load data processing. This course is one of a series that prepares you for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Data Workloads

Course Number:
it_clazdataf_01_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Data Workloads

  • discover the key concepts covered in this course
  • describe workload management
  • identify the need for data solutions
  • identify types of data storage
  • recognize characteristics of transactional workloads
  • recognize characteristics of analytical workloads
  • describe the purpose and features of Azure Batch
  • describe real time processing
  • differentiate between batch data and streaming data
  • describe relational databases
  • summarize the key concepts covered in this course

Overview/Description
Data workloads refer to the system's ability to handle and process work. In this course, you'll learn about core data workloads and workload management, including the need for data solutions and the various types of data storage. You値l then explore transactional and analytical workloads, Azure Batch, and real time processing. Finally, you値l learn about the differences between batch data and streaming data and the fundamentals of relational data. This course is one in a collection that prepares learners for Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Modern Data Warehousing

Course Number:
it_clazdataf_12_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Modern Data Warehousing

  • discover the key concepts covered in this course
  • describe modern data warehousing
  • describe benefits of modern data warehousing
  • describe modern data warehousing architecture
  • describe Azure Data Factory
  • describe Azure Data Lake
  • describe Azure Databricks
  • describe Azure Analysis Services
  • describe Azure HDInsights
  • describe the Distributed Data Engineering Toolkit
  • summarize the key concepts covered in this course

Overview/Description
Modern data warehousing lets you bring your data together at any scale and provide insights through analytics. This course, you値l learn about the components of a modern data warehouse and its architecture and how it can benefit your organization. You値l start by learning about modern data warehousing, and then the data warehousing architecture. You'll then learn about Azure Data Factory, Azure Data Lake, and Azure Databricks. You値l then go on to explore Azure Analysis Services and Azure HDInsights. Finally, you'll discover Azure Distributed Data Engineering Toolkit. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Non-relational Data Management

Course Number:
it_clazdataf_10_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Non-relational Data Management

  • discover the key concepts covered in this course
  • use the Azure portal to manage Cosmos DB
  • use Azure Resource Manager templates to manage Cosmos DB
  • use Azure PowerShell to manage Cosmos DB
  • use the Azure CLI to manage Cosmos DB
  • describe Cosmos DB firewall
  • describe Cosmos DB authentication
  • describe Cosmos DB security
  • use Azure Cosmos DB Explorer
  • describe Cosmos DB geo-replication
  • identify Cosmos DB IP access control policy issues
  • identify Cosmos DB .NET SDK issues
  • identify Cosmos DB Java SDK issues
  • summarize the key concepts covered in this course

Overview/Description
Non-relational data does not use SQL for queries and instead it uses other programming languages and constructs to query the data. This course covers basic management tasks for non-relational data, including how to deploy data using the Azure portal, Azure Resource Manager Templates, Azure PowerShell, and the Azure CLI. You'll learn about Cosmos DB firewall, authentication, and other security components. Finally, you'll explore Azure Cosmos DB Explorer and Geo-replication, as well as various issues that may arise with access control, .NET SDKs, and Java SDKs. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Non-relational Data Services

Course Number:
it_clazdataf_08_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Non-relational Data Services

  • discover the key concepts covered in this course
  • describe how to provision non-relational data services
  • describe how to configure non-relational data services
  • describe how to provision other non-relational data services
  • describe features, concepts, and system properties of Azure Table Storage
  • describe the features of Azure Blob Storage, how to access storage resources, and migrating data and system properties for Azure Blob Storage
  • describe how to create an Azure Storage Container and upload, download, and delete a Blob
  • describe features, protocols, uses, and benefits of Azure File Storage
  • describe how to manage Azure File Storage including using Azure Storage Explorer, generating SAS tokens, and uploading files to Azure File Storage
  • summarize the key concepts covered in this course

Overview/Description
Non-relational data repositories can store data in its original format and allow fast storage and retrieval access. In this course, you'll learn about the non-relational data services, including Azure Table Storage, Azure Blob Storage, and Azure File Storage. You'll also learn how to provision and configure non-relational data services and manage Azure Blob Storage and Azure File Storage. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Non-relational Data Workloads

Course Number:
it_clazdataf_07_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Non-relational Data Workloads

  • discover the key concepts covered in this course
  • describe characteristics of non-relational data
  • identify when to use non-relational vs. relational data
  • list the different types of non-relational data
  • describe how CSV and JSON files are used for non-relational data
  • identify the requirements of non-relational data stores
  • describe free-form text for search, including architecture and challenges
  • describe time series solutions, including benefits and challenges
  • summarize the key concepts covered in this course

Overview/Description

Non-relational databases use a storage model that is optimized for the data being stored. In this course, you'll learn about characteristics of non-relational data, including the different types of non-relational data. You'll learn when to use non-relational versus relational data. Next, you'll explore the use of CSV and JSON files for non-relational data and the requirements of non-relational data stores. You値l examine free-form text for search, including architecture and challenges. Finally, you'll learn about time series solutions, including their benefits and challenges. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.



Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Provisioning & Configuring Relational Data Services

Course Number:
it_clazdataf_05_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Provisioning & Configuring Relational Data Services

  • discover the key concepts covered in this course
  • describe provisioning relational data services
  • provision a Microsoft Azure SQL Database
  • provision Azure Database for PostgreSQL
  • provision Azure Database for MySQL
  • provision Azure Database for MariaDB
  • configure a Microsoft Azure SQL Database
  • configure Azure Database for PostgreSQL
  • configure Azure Database for MySQL
  • configure Azure Database for MariaDB
  • summarize the key concepts covered in this course

Overview/Description
Azure database services are fully managed, which frees up valuable time otherwise spent on managing them. In this course, you'll learn how to provision relational data services and a Microsoft Azure SQL Database. You値l explore how to provision a Microsoft Azure SQL Database for PostgreSQL, MySQL, and MariaDB. Next, you'll discover how to configure a Microsoft Azure SQL Database. Finally, you値l learn how to configure Azure Database for PostgreSQL, MySQL, and MariaDB. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900 Azure Data Fundamentals: Relational Data Management

Course Number:
it_clazdataf_04_enus
Lesson Objectives

DP-900 Azure Data Fundamentals: Relational Data Management

  • discover the key concepts covered in this course
  • use different methods for deploying relational data
  • describe Azure SQL Database uses and features
  • recognize Azure SQL Database security features
  • use Azure AD authentication for security
  • use Azure Data Studio as a query tool
  • use SQL Server Management Studio as a query tool
  • use the sqlcmd utility as a query tool
  • describe SQL Server on Azure Virtual Machine
  • describe Azure Managed Instance features
  • describe Azure Synapse Analytics components and features
  • identify different Azure SQL connectivity errors
  • identify different Azure SQL connectivity issues
  • summarize the key concepts covered in this course

Overview/Description
Relational data management ensures cloud database systems are versatile and functionable. In this course, you'll explore how to work with relational data on Azure, including basic management tasks for relational data such as SQL database and the security features within. You'll then learn about Azure Data Studio, Azure SQL Server Management Studio, SQL Server, and the sqlcmd utility. Finally, you'll learn about SQL Managed Instance, Azure Synapse Analytics, as well as different connectivity issues such as authentication or firewall. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.

Target

Prerequisites: none

DP-900: Azure Data Fundamentals: Relational Data Workloads

Course Number:
it_clazdataf_03_enus
Lesson Objectives

DP-900: Azure Data Fundamentals: Relational Data Workloads

  • discover the key concepts covered in this course
  • describe the characteristics of relational data
  • identify the different data store models
  • use indexes in an Azure SQL relational database
  • use views in an Azure SQL relational database
  • identify the different delivery models for Azure relational data
  • describe Azure Platform as a Service
  • describe Azure Infrastructure as a Service
  • describe Azure Software as a Service
  • describe online transaction processing (OLTP)
  • describe online analytical processing (OLAP)
  • summarize the key concepts covered in this course

Overview/Description

Relational data is stored in tables, which allows users to easily categorize and query the data. In this course, you'll learn about the characteristics of relational data and different relational databases. You'll explore how to use indexes and views in a relational database, as well as the different delivery models for relational data. Next, you'll examine Platform as a Service, Infrastructure as a Service, and Software as a Service. Finally, you'll learn about online transaction and analytical processing. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.



Target

Prerequisites: none

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