Azure Data Engineer & Microsoft Fabric Analytics
Azure Data Engineer Associate (DP-203)
Azure for the Data Engineer
➢ Cloud Computing basics
➢ Introduction to Microsoft Azure
➢ Applications of Azure
➢ Azure Services
➢ Understanding Data
➢ On-premises vs Cloud-based servers
➢ Azure Data Engineer roles & tasks
➢ Data Engineering processes
➢ Use cases for the Cloud
Data Services for the Azure Data Engineer
➢ Azure Datalake Storage (ADLS) gen2
➢ Azure Blob Storage
➢ Azure SQL database
➢ Azure Data Factory
➢ Azure Databricks
➢ Azure Synapse Analytics
Data Storages on Azure
➢ File stores
➢ Relational data store
➢ Non-Relational data stores
➢ Azure Blob storage
➢ NoSQL & Azure Cosmos DB
➢ Azure Blob Storage
➢ Azure Data Lake Storage
➢ Why Data Lake
➢ Data Lake architecture
➢ Azure SQL Database
➢ Azure database for MySQL
➢ Azure database for MariaDB
➢ Azure database for PostgreSQL
➢ Azure Synapse Analytics
Data Integration, CI/CD Pipelines using Azure Data Factory (ADF)
➢ Introduction to ADF
➢ ETL vs ELT
➢ Data Integration Patterns
➢ Code-free ETL as a Service
➢ ADF Components
➢ Linked Services & Connectors
➢ Integration Runtime
➢ Pipelines and activities
➢ Data Ingestion methods
➢ Data Movement
➢ Data Transformations
➢ Control flows
➢ Scheduling & Triggering Pipelines
➢ Monitoring Pipelines
➢ CI/CD Pipelines with ADF
Data Engineering with Azure Databricks
➢ Introduction to Azure Databricks
➢ Databricks runtime engine
➢ Cluster & Workspace
➢ Databricks file system (DBFS)
➢ Accessing data using Databricks UI
➢ Accessing data with Databricks Notebooks
➢ Working with different Data formats
➢ Data Analysis using Apache Spark
➢ Processing data with PySpark
➢ Apache Spark Ecosystem
➢ Apache Spark architecture
➢ Spark Transformations & Actions
➢ Working with Spark SQL
➢ Delta Lakes & Tables
➢ Lakehouse architecture
➢ Structured Streaming
➢ Scheduling Databricks jobs using ADF pipelines
Fabric Data Engineer Associate (DP-700)
Data Engineering using Microsoft Fabric
➢ Introduction to Microsoft Fabric
➢ Understanding the Fabric Analytics platform
➢ Ingesting data using Pipelines in Fabric
➢ Introduction to Dataflows gen2
➢ Ingest and Transform data using Dataflows gen2
➢ Analyze data with Apache Spark in Fabric
➢ Working with Lakehouse in Fabric Analytics
➢ Working with Delta Tables
➢ Real-Time Dashboards in Fabric
➢ Analyzing data in a Data Warehouse in Microsoft Fabric
➢ Load, Query & Monitor data in a Data Warehouse
➢ Perform Data Analysis using Fabric Notebooks
➢ Perform Data Analysis using Power BI
➢ Workspace and Permissions
➢ Implementing Row-level & Column-level security
➢ Data Access Roles and Access controls
Hands-on Real-time ADE Scenarios
➢ Exploring Data services on Azure Portal
➢ Creating and setting-up Blob & ADLS accounts
➢ Creating Linked Service, Integration Runtime in ADF
➢ Creating ETL/ELT Pipelines in Azure Data Factory
➢ Working with Control Flow activities in ADF Pipelines
➢ Working with Data Flow Transformations in ADF Pipelines
➢ Ingesting various File sources using ADF pipelines
➢ Ingesting On-prem SQL Server data to Azure SQL database
➢ Ingesting multiple file sources using a single Pipeline
➢ Ingesting multiple SQL tables using single Pipeline
➢ Copying data from Blob storage to ADLS
➢ Copying data from Azure SQL database to ADLS
➢ Copying data from Blob storage to Azure SQL database
➢ Implementing Batch load & Sequential load
➢ Incremental loading and Change data capture
➢ SCD1 Implementation using ADF Mapping dataflows
➢ SCD2 Implementation using ADF Mapping dataflows
➢ Creating Azure Databricks Workspace and Cluster
➢ DBFS and DBUTILS
➢ Analyzing data with Databricks Notebooks
➢ ADLS integration with Azure Databricks
➢ Mounting ADLS to Azure Databricks using Access Keys
➢ Secret scopes, Service Principal & SAS Tokens
➢ Creating Delta Tables
➢ Working with Lakehouse architecture
Real-time Projects
✓ Data Migration using ADF (migrating on-prem SQL Server data to
Azure)
✓ End-to-End Pipelines, data processing using ADF and Azure Databricks
✓ Incremental load & CDC
✓ Data Ingestion using Pipelines in Microsoft Fabric
✓ Working with Apache Spark in Fabric
✓ Implementing Data Warehouse in Fabric
✓ Analyzing data with Power BI in Fabric
✓ Loading data from AWS S3 to ADLS using ADF Pipeline
✓ Loading data from ADLS to Snowflake
✓ CI/CD pipelines using ADF
Bonuses
➢ ADE Interview Questions and Answers
➢ Mock Interviews
➢ Placement Assistance
➢ ADE Certification (DP700) Support
➢ Databricks certification support
➢ Resume/CV Preparation
➢ LinkedIn Profile Optimization