Data Warehousing with Azure E-Learning

• Language: English
• Target audience: The Data Warehousing with Azure training course is aimed at professionals and IT personnel engaged in designing, implementing and managing data warehousing solutions using Azure technologies.
• Required Knowledge Level: A general understanding of Microsoft Azure and the basics of cloud computing is very helpful when taking Data Warehousing with Azure training course
• Course duration: 6:37 hours (depending on personal speed)
• Online access: 24/7, 365 days after activation
• Award Winning E-learning
• Complete training for the official Exam
• User-friendly environment
• Certificate of Participation included

Data Warehousing With Azure Training

Data Warehousing with Azure E-Learning Training is an online training program designed to teach professionals and IT personnel how to build and manage data warehousing solutions using Microsoft Azure technologies.

This self-paced learning experience includes 1 year of 24/7 access to in-depth learning modules, instructional videos, and hands-on exercises that walk learners through key aspects of cloud-based data warehousing using tools like Azure Synapse Analytics, Data Lake, Data Factory, and SQL Database.

Why Choose This Training?

• Step-by-step guide to designing and deploying data warehouses on Azure
• Flexible online format – study anytime, anywhere
• Interactive materials, hands-on labs, and expert-led video instruction
• Gain in-demand skills in Azure data services and cloud analytics
• Includes progress tracking and certificate of participation

Who Should Attend?

• Data engineers, BI professionals, and IT specialists
• Analysts and developers building scalable data solutions
• Organizations migrating to a cloud-based data infrastructure
• Professionals looking to expand skills in Microsoft Azure data tools
• Anyone involved in data storage, reporting, or analytics

Demo Data Warehousing with Azure Training

Course content

Data Warehousing with Azure: Architecture & Modeling Techniques

Course: 1 Hour, 18 Minutes

• Data Warehouse Features
• Data Warehouse Architectures
• Data Warehouse Alternatives
• Data Warehouse Generation
• Variations of Data Warehouse
• Federated Data Warehouse Features
• Star Schema and Data Mart Approach
• Data Warehouse Lifecycle Phases
• Metadata Concepts in Data Warehouse
• Structured and Unstructured Data
• Structured and Unstructured Data - Examples
• Analytics and Reporting Approach
• Cloud Data Warehouse
• Hybrid Data Warehouse Architecture
• Exercise: Implementing Data Warehouse Features

Data Warehousing with Azure

Course: 1 Hour, 8 Minutes

• SQL Data Warehouse Features and Architecture
• MPP and Workload Management
• Creating SQL Data Warehouse
• Connect and Query SQL Data Warehouse
• Create and Query SQL Data Warehouse using PowerShell
• Data Warehouse Design
• Design and Best Practices for SQL Data Warehouse
• Pause and Resume Functionality
• Scale Compute in Azure SQL Data Warehouse
• ELT Process for Azure SQL Data Warehouse
• Exercise: Working with SQL Data Warehouse

Data Warehousing with Azure

Course: 1 Hour, 27 Minutes

• Decision Making
• Data Warehouse Modeling
• Tables in SQL Data Warehouse
• T-SQL Commands for Table Creation
• Unsupported Features
• Distributed Table Concepts
• Data Loading Techniques
• Load Data to SQL Data Warehouse
• Load Data Using Azure Data Factory
• Load Data Using SQL Server Integration Services
• Import and Export Data from SQL Data Warehouses
• T-SQL Loops in SQL Data Warehouse
• Stored Procedure Essential Elements
• Transaction Management Concepts
• Architectural Abstraction Using Views
• Workload Management and Performance
• Exercise: Working with Tables and Data

Data Warehousing with Azure

Course: 45 Minutes

• Azure Analysis Services
• Create an Analysis Services Server Using PowerShell
• Create an Analysis Services Server Using Portal
• Add Models to the Analysis Server
• Create Reports Using Power BI
• Exploring Data Using Excel and Power BI
• Power BI and SQL Data Warehouse
• AdventureWorks Data Warehouse
• Azure Data Lake and Power BI
• Exercise: Preparing Data and Creating Reports

Data Warehousing with Azure

Course: 59 Minutes

• Goals and Features of a Data Lake
• Introducing the Azure Data Lake
• Azure Gen1 Data Lake Storage
• Azure Gen2 Data Lake Storage
• Gen1 Azure Data Lake Storage Using Portal
• Gen1 Azure Data Lake Storage Using PowerShell
• Gen1 Azure Data Lake Storage Using VSCode and CLI
• Azure Storage Explorer
• Gen2 Azure Data Lake Storage Creation
• Loading Data in an Azure Data Lake
• Data Lake and SQL Data Warehouse
• Comparing V1 and V2 Azure Data Factory
• Exercise: Creating the Azure Data Lake Storage

Data Warehousing with Azure

Course: 1 Hour

• Azure Data Lake and Big Data
• Ingesting Data in the Data Store
• Data Sources for Azure Data Lake
• Data Loading Approaches for Huge Data
• Moving Data from a Data Lake to Other Sources
• Moving Data Using AdlCopy
• Using the Offline Copy Method
• Security Mechanism for Azure Data Lake
• Securing Data in Azure Data Lake
• Tuning Data Lake
• Log Analytics
• Implementing Log Analytics
• Exercise: Moving Offline Data  

What is Data Warehousing with Azure?

Data Warehousing Azure refers to the use of Azure, Microsoft's cloud computing platform, to build and manage data warehousing solutions. A data warehouse is a data storage system used to collect, organize and analyze large amounts of structured and unstructured data from various sources, enabling businesses to gain valuable insights and decision support.

With Azure, Microsoft offers a suite of services and tools specifically designed to support data warehousing capabilities in the cloud.

10 benefits of Data Warehousing with Azure

1. Scalability: Azure provides scalable and flexible solutions for managing large amounts of data, making it easy to expand and scale data warehouses.
2. Reliability: Azure has a robust and reliable infrastructure that ensures high availability and continuous uptime, which is essential for data warehousing.
3. Security: Azure offers multiple layers of security, including network security, access control, authentication and authorization, keeping data safe in the cloud.
4. Integration: Azure integrates seamlessly with existing on-premises systems and other Azure services, making it easy to collect and combine data from different sources.
5. Analytical capability: Azure offers powerful built-in analytics capabilities, including advanced machine learning and artificial intelligence, enabling businesses to extract valuable insights from their data.
6. Reduce costs: Azure offers pay-per-use models and other cost-saving solutions that can help lower a data warehouse's total cost of ownership.
7. Easy implementation: Azure offers predefined templates, wizards and quick-start guides that allow users to quickly and easily deploy a data warehouse.
8. Easy management: Azure provides an intuitive and user-friendly interface for managing data warehouses, making it easy to monitor database health, performance and configuration.
9. Flexibility: Azure offers flexible and customizable data warehouse architectures, allowing companies to choose the best solution for their specific needs.
10. Innovation: Azure continues to evolve, constantly offering new and innovative data warehousing solutions, ensuring that businesses always have access to the latest and greatest technologies.

Why is Data Warehousing with Azure important?

Data Warehousing with Azure is important because it allows companies to store and manage large amounts of data in one central location. This simplifies data management and enables advanced analytics and insights. With Azure, businesses can take advantage of scalability, flexibility and reliability to meet their data needs. It offers integrated analytics capabilities and advanced security features to protect data. Data Warehousing with Azure also drives innovation by offering continuous updates and new technologies that businesses can use to extract value from their data.

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