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DP 203: Data Engineering on Microsoft Azure
Quick Facts
| particular | details | ||||
|---|---|---|---|---|---|
|
Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
|
Frequency of Classes
Weekends
|
Course and certificate fees
Fees information
₹ 17,995 ₹19,995
The fees for the course DP 203: Data Engineering on Microsoft Azure is -
| Head | Amount |
| Original price | Rs. 19,995 |
| Discounted price | Rs. 17,995 |
* No Cost EMI starts at Rs. 5,999 / month
certificate availability
Yes
certificate providing authority
Edureka
The syllabus
Introduction to Microsoft Azure and its Services
Topics
Hands-on
- Create a free tier Azure account
- Create a web app service using Azure Portal
- Create and Deploy ARM templates
- Manage Azure Storage account
- Manage Azure Cost and Billing
Skills
- Creating ARM templates
- Accessing Azure Storage Service
- Azure Cost and Billing Services
Introduction to Azure Data Engineering
Topics
- Understand the evolving world of data
- Data abundance
- Understanding the Data Engineering Problem
- Understand job responsibilities
- Understanding Data Engineering Processing - Extract Transform and Load
- Overview of Azure Data Engineering Services
- Understand data storage in Azure Storage
- Understand data storage in Azure Data Lake Storage
- Understand Azure Cosmos DB
- Understand Azure SQL Database
- Understand Azure Synapse Analytics
- Understand Azure Stream Analytics
- Understand Azure HDInsight
- Understand other Azure data services
Hands-on
- Navigating through Azure data engineering services
Skills
- Analyzing Data Engineering Process
- Understanding Azure Services
Storing Data in Azure
Topics
- How to choose an Azure Storage Service in Azure
- Create an Azure Storage Account
- Connect an app to Azure Storage API
- Connect to your Azure storage account
- Explore Azure Storage security features
- Understand storage account keys
- Understand shared access signatures
- Control network access to your storage account
- Understand Advanced Threat Protection for Azure Storage
- Explore Azure Data Lake Storage security features
- Introduction to Blob storage
- What are blobs?
- Design a storage organization strategy
Hands-on
- Add the storage client library to your app
- Add Azure Storage configuration to your app
- Connect your application to your Azure Storage account
- Create Azure storage resources
- Configure and initialize the client library
- Get blob references
- Blob uploads and downloads
Skills
- Working with Azure Storage
- Configuring Security in Azure Storage
- Storing blob data in Azure Storage
Azure Data Factory Part - I
Topics
- Integrate data with Azure Data Factory or Azure Synapse Pipeline
- Understand Azure Data Factory
- Describe data integration patterns
- Explain the data factory process
- Understand Azure Data Factory components
- Azure Data Factory security
- Set-up Azure Data Factory
- Create linked services
- Create datasets
- Create data factory activities and pipelines
- Manage integration runtimes
- Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
- List the data factory ingestion methods
- Describe data factory connectors
- Understand data ingestion security considerations
Hands-on
- Use the data factory copy activity
- Manage the self hosted integration runtime
- Setup the Azure integration runtime
Skills
- Working with Azure Data Factory
- Integrating Azure Data Factory
- Azure Data Factory security
- Implementing Data Factory connectors
Azure Data Factory Part - II
Topics
- Explain Data Factory transformation methods
- Describe Data Factory transformation types
- Exercise - Author an Azure Data Factory mapping data flow
- Debug mapping data flow
- Exercise - Use Data Factory wrangling data
- Exercise - Use compute transformations within Data Factory
- Exercise - Integrate SQL Server Integration Services packages within Data Factory
- Describe slowly changing dimensions
- Choose between slowly changing dimension types
- Exercise - Design and implement a Type 1 slowly changing dimension with mapping data flows
- Understand data factory control flow
- Work with data factory pipelines
- Debug data factory pipelines
- Add parameters to data factory components
- Exercise - Integrate a Notebook within Azure Synapse Pipelines
- Execute data factory packages
- Describe SQL Server Integration Services
- Understand the Azure-SIS integration runtime
- Set-up Azure-SIS integration runtime
- Run SSIS packages in Azure Data Factory
- Migrate SSIS packages to Azure Data Factory
- Configure a git repository with a development factory
- Create and merge a feature branch
- Deploy a release pipeline
- Visually monitor pipeline runs
- Integrate with Azure Monitor
- Set up alerts
- Rerun pipeline runs
Hands-on
- Author an Azure Data Factory mapping data flow
- Use Data Factory wrangling data
- Use compute transformations within Data Factory
- Integrate SQL Server Integration Services packages within Data Factory
- Design and implement a Type 1 slowly changing dimension with mapping data flows
- Integrate a Notebook within Azure Synapse Pipelines
Skills
- Implementing Data Factory transformations
- Implementing slowly changing dimensions
- Working with SQL server integration
- Configuring a git repository
- Integrating Azure monitor and set up alerts
Azure Synapse Analytics Part - I
Topics
- What is Azure Synapse Analytics5 min
- How Azure Synapse Analytics works8 min
- When to use Azure Synapse Analytics4 min
- Exercise - Explore Azure Synapse Analytics
- Create Azure Synapse Analytics workspace4 min
- Exercise - Create and manage Azure Synapse Analytics workspace4 min
- Describe Azure Synapse Analytics SQL5 min
- Explain Apache Spark in Azure Synapse Analytics7 min
- Exercise - Create pools in Azure Synapse Analytics9 min
- Orchestrate data integration with Azure Synapse pipelines7 min
- Exercise-Identifying Azure Synapse pipeline components8 min
- Visualize your analytics with Power BI7 min
- Understand hybrid transactional analytical processing with Azure Synapse Link
- Use Azure Synapse Studio
Hands-on
- Explore Azure Synapse Analytics
- Create pools in Azure Synapse Analytics
- Identifying Azure Synapse pipeline components
Skills
- Working with Azure Synapse Analytics
- Managing Azure Synapse Analytics workspace
- Querying data and Visualizing analytics
- Working with Azure Synapse pipeline components
Azure Synapse Analytics Part - II
Topics
- Understand the Azure Synapse Analytical processes
- Explore the Data hub
- Explore the Develop hub
- Explore the Integrate hub
- Explore the Monitor hub
- Explore the Manage hub
- Describe a Modern Data Warehouse
- Define a Modern Data Warehouse Architecture
- Design ingestion patterns for a Modern Data Warehouse
- Understand data storage for a Modern Data Warehouse
- Understand file formats and structure for a modern data warehouse
- Prepare and transform data with Azure Synapse Analytics
- Serve data for analysis with Azure Synapse Analytics
Hands-on
- Create a new data flow or dataset, and manage the file
- Use the Monitor hub to view pipeline and trigger runs, view the status of the various integration runtimes
Skills
- Working with various types of hubs
Work with Data Warehouses using Azure Synapse Analytics - Part I
Topics
- Describe a modern data warehouse
- Define a modern data warehouse architecture
- Exercise - Identify modern data warehouse architecture components
- Design ingestion patterns for a modern data warehouse
- Understand data storage for a modern data warehouse
- Understand file formats and structure for a modern data warehouse
- Prepare and transform data with Azure Synapse Analytics
Hands-on
- Serve data for analysis with Azure Synapse Analytics
- Design a data warehouse schema
- Create data warehouse tables
- Load data warehouse tables
- Query a data warehouse
Skills
- Designing a Modern Data Warehouse Architecture
- Building a Data Warehouse
- Working with different file formats
- Preparing and transforming data
Work with Data Warehouses using Azure Synapse Analytics - Part II
Topics
- Understand data load design goals
- Explain load methods into Azure Synapse Analytics
- Manage source data files
- Manage singleton updates
- Set-up dedicated data load accounts
- Implement workload management
- Simplify ingestion with the Copy Activity
- Understand performance issues related to tables
Hands-on
- Data Loading in Azure Synapse Analytics
- Data Ingestion using Copy Activity
- Implement workload management
- Understand performance issues related to tables
Skills
- Loading data using Azure Synapse Analytics
- Implementing workload management
Optimizing Data Queries in Azure
Topics
- Understand table distribution design
- Use indexes to improve query performance
- Understand query plans
- Create statistics to improve query performance
- Improve query performance with materialized views
- Use read committed snapshot for data consistency
- How does statistics affect a query plan?
- Describe the integration methods between SQL and spark pools in Azure Synapse Analytics
- Understand the use-cases for SQL and spark pools integration
- Exercise: Integrate SQL and spark pools in Azure Synapse Analytics
- Externalize the use of spark pools within Azure Synapse Workspace
- Transfer data outside the synapse workspace using the PySpark connector
- Explore the development tools for Azure Synapse Analytics
- Understand transact-SQL language capabilities for Azure Synapse Analytics
Hands-on
- Use table distribution and indexes to improve performance
- Optimize common queries with result-set caching
- Work with windowing functions
- Work with approximate execution
- Work with JSON data in SQL pools
- Encapsulate transact-SQL logic with stored procedures
- Authenticate in Azure Synapse Analytics
- Transfer data between SQL and spark pool in Azure Synapse Analytics
- Authenticate between spark and SQL pool in Azure Synapse Analytics
Skills
- Optimizing data queries in Azure
- Authenticating in Azure Synapse Analytics
- Working with SQL and Spark pool
Managing Workloads in Azure Synapse Analytics
Topics
- Scale compute resources in Azure Synapse Analytics
- Pause compute in Azure Synapse Analytics
- Manage workloads in Azure Synapse Analytics
- Use Azure Advisor to review recommendations
- Use dynamic management views to identify and troubleshoot query performance
- Understand skewed data and space usage
- Understand network security options for Azure Synapse Analytics
- Configure Conditional Access
- Configure authentication
- Manage authorization through column and row level security
- Exercise - Manage authorization through column and row level security
- Manage sensitive data with Dynamic Data Masking
- Implement encryption in Azure Synapse Analytics
Hands-on
- Manage authorization through column and row level security
Skills
- Managing workloads in Azure Synapse Analytics
- Authentication and authorization in Azure Synapse Analytics
- Implementing encryption in Azure Synapse Analytics
Deep Dive into Azure Databricks
Topics
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Use Apache Spark in Azure Databricks
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Get Started with Delta Lake
- Create Delta Lake tables
- Create and query catalog tables
- Use Delta Lake for streaming data
- Get started with SQL Warehouses
- Create databases and tables
- Create queries and dashboards
- Understand Azure Databricks notebooks and pipelines
- Create a linked service for Azure Databricks
- Use a Notebook activity in a pipeline
- Use parameters in a notebook
Hands-on
- Explore Azure Databricks
- Run an Azure Databricks Notebook with Azure Data Factory
- Use a SQL Warehouse in Azure Databricks
- Use Delta Lake in Azure Databricks
- Use Spark in Azure Databricks
Skills
- Working with Azure Databricks
- Running interactive and scheduled data analysis workloads
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