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Data ingestion is crucial in analytics. Microsoft Fabric's Data Factory offers Dataflows for visually creating multi-step data ingestion and transformation using Power Query Online.

Units in this learning path:

• Introduction
• Dataflows Gen 2
• Explore Dataflows Gen 2
• Dataflow Pipeline
• Exercise
• Knowledge Check
• Summary

Products: Fabric

Roles: Data Analyst, Data Engineer

Level: Intermediate

Subjects: Data Analytics, Data Engineering, Data Integration

Duration: 60 minutes

Learn how to ingest data into Customer Insights - Data.

Units in this learning path:

• 1 Introduction
• 2 Power Query
• 2b Clean Transform Load Data
• 3 Common Data Model
• 4 Dataverse
• 5 Work with Data
• 6 Refresh
• 8 Check
• 9 Summary

Products: Dynamics 365, Customer Insights Data

Roles: Functional Consultant, Business User, Administrator

Level: Intermediate

Subjects: Data Analytics, Customer Relationship Management

Duration: 45 minutes

Learn how to ingest data from diverse sources into Unity Catalog tables in Azure Databricks using managed connectors, notebooks, SQL commands, streaming, and declarative pipelines.

Units in this learning path:

• Introduction
• Ingest Data Lakeflow Connect
• Ingest Data Notebooks
• Ingest Data SQL Methods
• Ingest Data Cdc Feed
• Ingest Data Spark Structured Streaming
• Ingest Data Auto Loader
• Ingest Data Lakeflow Declarative Pipelines
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 56 minutes

Explore how Microsoft Fabric enables you to ingest and orchestrate data from various sources (such as files, databases, or web services) through dataflows, notebooks, and pipelines.

Modules in this learning path:

• Ingest Dataflows Gen2 Fabric
• Use Data Factory Pipelines Fabric
• Use Apache Spark Work Files Lakehouse
• Query Data Kql Database Microsoft Fabric

Products: Fabric

Roles: Data Analyst, Data Engineer, Data Scientist

Level: Intermediate

Subjects: Big Data, Data Analytics, Data Engineering, Data Integration, Data Management

Duration: 289 minutes

Azure Stream Analytics provides a real-time data processing engine that you can use to ingest streaming event data into Azure Synapse Analytics for further analysis and reporting.

Units in this learning path:

• Introduction
• Stream Ingestion Scenarios
• Configure Inputs Outputs
• Define Query
• Run Job Ingest
• Exercise Ingest Streaming Data
• Knowledge Check
• Summary

Products: Azure Stream Analytics, Azure Synapse Analytics

Roles: Data Engineer

Level: Intermediate

Subjects: Data Analytics, Data Engineering

Duration: 74 minutes

Do you want to know how to initialize data during extension installation for Microsoft Dynamics 365 Business Central? Initializing data when you're installing an extension automate many steps that you must otherwise perform manually. By automating this process, you can quickly set up an extension and it becomes more user-friendly.

Units in this learning path:

• 1 Introduction
• 2 Install Logic
• 3 Exercise
• 4 Check
• 5 Summary

Products: Dynamics 365, Dynamics Business Central

Roles: Developer

Level: Beginner

Subjects: Data Engineering

Duration: 32 minutes

Learn to integrate Azure AI Services with Azure Database for PostgreSQL to add intelligent features like summarization and sentiment analysis.

Units in this learning path:

• Introduction
• Summarize Data Azure AI Services Azure Database Postgresql
• Perform Sentiment Analysis Opinion Mining Azure Database Postgresql
• Extract Insights Azure Language Azure Database Postgresql
• Translate Text Azure Translator Azure Database Postgresql
• Exercise Use Azure AI Services Azure Database Postgresql
• Use Azure Machine Learning Inference Azure Database Postgresql
• Exercise Perform Inference Azure Machine Learning
• Knowledge Check
• Summary

Products: Azure, Azure Database Postgresql

Roles: Developer, Data Engineer, Solution Architect

Level: Intermediate

Subjects: Databases, Artificial Intelligence, Cloud Computing

Duration: 72 minutes

Integrate Azure Cosmos DB for NoSQL with Azure services

Modules in this learning path:

• Consume Azure Cosmos Db SQL API Change Feed Using Sdk
• Handle Events Azure Functions Azure Cosmos Db SQL API Change Feed
• Search Azure Cosmos Db SQL API Data Azure Cognitive Search

Products: Azure Cosmos Db, Azure Cognitive Search

Roles: Developer

Level: Intermediate

Subjects: Databases, Artificial Intelligence

Duration: 117 minutes

Integrate SQL and Apache Spark pools in Azure Synapse Analytics

Units in this learning path:

• Introduction
• Describe Integration Methods Between SQL
• Understand Use Cases for SQL Integration
• Authenticate
• Transfer Data Between SQL Spark Pool
• Authenticate Between Spark SQL Pool
• Exercise Integrate SQL
• Externalize Use of Spark Pools Within Workspace
• Transfer Data Outside Synapse Workspace Using Pyspark Connector
• Knowledge Check
• Summary

Products: Azure Synapse Analytics

Roles: Data Engineer

Level: Intermediate

Subjects: Databases

Duration: 33 minutes

Integrate data with Azure Data Factory or Azure Synapse Pipeline

Units in this learning path:

• Introduction
• Understand
• Describe Data Integration Patterns
• Explain Process
• Understand Components
• Security
• Set Up
• Create Linked Services
• Create Datasets
• Create Activities Pipelines
• Manage Integration Runtime
• Knowledge Check
• Summary

Products: Azure Data Factory, Azure Synapse Analytics

Roles: Data Engineer, Data Scientist

Level: Beginner

Subjects: Data Analytics

Duration: 62 minutes

Finance and operations apps are integrated with Microsoft Azure to help power many of its built-in capabilities, such as search and intelligence. This module will focus on custom cloud integrations that you can build that are unique to your own project integration needs.

Units in this learning path:

• 1 Introduction
• 2 Logic Apps
• 3 Power
• 4 Enterprise
• 5 Automate
• 6 Machine Learn
• 7 Connect External
• 8 Optimize
• 9 Check
• 10 Summary

Products: Dynamics 365, Dynamics Finance, Dynamics Scm

Roles: Developer

Level: Advanced

Subjects: Devops, Data Management

Duration: 32 minutes

This credential earner has the advanced skills and ability to integrate backend servers with MySQL and MongoDB, applying CRUD operations and aggregation pipelines for efficient data management. The individual can design basic entity relationship (ER) diagrams, write MySQL queries, and use Mongoose to connect backend servers with MongoDB. The earner has practiced essential workplace skills.