DP 203: Data Engineering on Microsoft Azure

BY
Edureka

Mode

Online

Duration

6 Weeks

Fees

₹ 17995 19995

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 -

HeadAmount
Original priceRs. 19,995
Discounted priceRs. 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
  • Azure Subscriptions
  • Azure Resources
  • Azure Free Tier Account
  • Azure Resource Manager
  • Azure Resource Manager Template
  • Azure Storage
  • Types of Azure Storage
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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