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Microsoft Azure is a leading cloud platform that provides a wide range of services, from infrastructure as a service (IaaS) to platform as a service (PaaS) and software as a service (SaaS). It helps organizations manage and deploy applications, services, and data in the cloud. If you’re looking to learn Azure, here’s a structured approach to training content that covers essential concepts and skills:
MS Azure Training Content Outline
Introduction to Cloud Computing
What is Cloud Computing?
- Definition and Types: Public, Private, and Hybrid Cloud
- Benefits of Cloud: Cost Efficiency, Scalability, Flexibility, High Availability
- Key Cloud Providers: Microsoft Azure, AWS, Google Cloud
Introduction to Microsoft Azure
What is Microsoft Azure?
- Overview of Azure Services and Products
- Azure Global Infrastructure (Regions, Availability Zones)
- Azure Resource Manager (ARM)
Introduction to Microsoft Azure
Azure Core Services
What is Microsoft Azure?
- Overview of Azure Services and Products
- Azure Global Infrastructure (Regions, Availability Zones)
- Azure Resource Manager (ARM)
Compute Services:
Azure Virtual Machines (VMs): Deploy and manage Windows and Linux VMs.
Azure App Services: Host web apps, APIs, and mobile backends.
Azure Functions: Serverless computing for event-driven applications.
Azure Kubernetes Service (AKS): Manage Kubernetes clusters.
Storage Services:
Azure Blob Storage: Object storage for unstructured data.
Azure File Storage: Managed file shares for cloud or on-premises deployments.
Azure Disk Storage: Persistent block storage for VMs.
Azure Storage Account Types: Standard vs Premium.
Networking:
Azure Virtual Networks (VNets): Isolated network environment.
Azure Load Balancer & Traffic Manager: Load balancing across VMs and services.
Azure VPN Gateway & ExpressRoute: Secure connectivity options for hybrid clouds.
Azure Firewall & Network Security Groups (NSG): Protecting cloud resources.
Azure Identity and Security
Azure Active Directory (AAD):
Users, Groups, and Roles management.
Identity and access management: Single Sign-On (SSO), Multi-factor Authentication (MFA)
Azure AD B2B and B2C (Business-to-Business, Business-to-Consumer scenarios).
Azure Security:
Azure Security Center: Threat protection and security management.
Azure Sentinel: Cloud-native SIEM for intelligent security analytics.
Azure Key Vault: Manage sensitive information like keys, secrets, and certificates.
Azure Databases
SQL Database:
Azure SQL Database: Managed relational database as a service.
Azure SQL Managed Instance: Hybrid cloud database solution.
NoSQL Databases:
Azure Cosmos DB: Globally distributed, multi-model database.
Azure Table Storage: Key-value pairs storage.
Azure Database for MySQL/PostgreSQL:
Managed services for popular open-source databases.
Azure Monitoring and Management
Azure Monitor:
Monitor the performance of applications, VMs, and network infrastructure.
Azure Log Analytics:
Collect and analyze log data from Azure resources.
Azure Automation:
Automate repetitive tasks using runbooks and scripts.
Azure Cost Management:
Monitor and manage Azure spending and budgeting.
Azure DevOps & Developer Tools
Azure DevOps:
Azure Repos: Version control with Git or Team Foundation Version Control (TFVC).
Azure Pipelines: Continuous integration and delivery (CI/CD) pipelines.
Azure Artifacts: Package management.
Azure DevTest Labs:
Rapid provisioning of dev/test environments.
Azure Artificial Intelligence (AI) and Machine Learning (ML)
Azure AI Services:
Azure Cognitive Services: Pre-built APIs for vision, speech, language, and decision-making models.
Azure Bot Services: Build intelligent bots for customer interaction.
Azure Machine Learning:
Build, train, and deploy ML models.
Azure ML Studio: No-code environment for ML projects.
Azure IoT (Internet of Things)
Azure IoT Hub:
Centralized platform for managing IoT devices and applications.
Azure IoT Central:
Fully managed IoT application platform.
Azure Governance and Compliance
Azure Policies:
Enforce organizational standards and regulations across Azure resources.
Azure Blueprints:
Package artifacts for environment setup and compliance.
Azure Cost Management and Billing:
Cost analysis, budgeting, and recommendations for cost optimization.
Azure Certifications Overview
Microsoft Certified: Azure Fundamentals (AZ-900)
Entry-level certification for understanding basic cloud concepts and core Azure services.
Microsoft Certified: Azure Administrator Associate (AZ-104)
For professionals managing Azure resources, including VMs, networking, and storage.
Microsoft Certified: Azure Developer Associate (AZ-204)
Focus on developing cloud applications and services.
Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
For professionals designing and implementing solutions in Azure.
Microsoft Certified: Azure Security Engineer Associate (AZ-500)
For managing security within Azure services and environments.
Hands-on Labs & Exercises
Setting Up Azure Services:
Deploying VMs using Azure Portal and Azure CLI.
Setting up and configuring an Azure Virtual Network.
Creating and managing Azure Storage Accounts and Blob Storage.
Implementing basic Identity and Access management using Azure AD.
Practical Use Cases:
Building a simple web application with Azure App Service.
Setting up a Kubernetes cluster on Azure with AKS.
Managing an Azure SQL Database with basic CRUD operations.
Online Training: Click here to apply
MS POWER BI
Training in MS Power BI: Unlocking the Power of Data
Microsoft Power BI is one of the most popular and powerful business intelligence (BI) tools available today, enabling organizations to analyze, visualize, and share their data in a more interactive and insightful way. Training in Power BI equips users with the skills to harness the full potential of this tool, transforming raw data into meaningful insights for informed decision-making.
Here’s a comprehensive guide on what Power BI training involves and why it’s so valuable:
Introduction to Power BI
Overview: Understanding Power BI's role in business intelligence, including its ability to transform data from various sources into interactive dashboards, reports, and insights.
Components of Power BI:
Power BI Desktop: For data modeling and report creation.
Power BI Service: For sharing and collaboration in the cloud.
Power BI Mobile: For accessing reports on mobile devices.
Power BI Gateway: For maintaining up-to-date data.
Connecting to Data
Data Sources: How to connect Power BI to various data sources (Excel, SQL Server, Azure, web data, APIs, and more).
Data Importing vs. Direct Query: Understanding the two primary ways to work with data in Power BI.
Power Query Editor: The tool used for transforming and cleaning data before visualizing it. This includes: 1) Filtering and sorting 2) Merging datasets 3) Handling missing data 4) Creating calculated columns
Data Modeling and Relationships
Building Relationships: How to create relationships between different datasets to enhance data analysis.
Data Types and Hierarchies: Understanding different data types and creating time- based hierarchies (e.g., Year > Quarter > Month > Day).
Creating Measures and Calculated Columns: Using DAX (Data Analysis Expressions) to create custom calculations, such as total sales, year-over-year growth, etc.
Normalization and Star Schema: Learning best practices for designing clean, efficient data models.
Visualizations and Reports
Creating Visualizations: Exploring a wide range of charts and visual elements, including bar charts, pie charts, maps, scatter plots, and more.
Formatting Visuals: Customizing the look and feel of reports, including colors, fonts, and layouts.
Interactivity in Reports: Adding slicers, filters, drill-through actions, and tooltips to create interactive reports.
Using Power BI Themes: How to apply consistent color schemes and styles across reports.
Dynamic Visuals: Creating visuals that update based on user input (e.g., slicers that change the data displayed).
Advanced Features and Techniques
DAX (Data Analysis Expressions): Advanced calculations using DAX formulas to create dynamic measures and metrics, such as Year-to-Date (YTD) calculations, running totals, and custom aggregations.
Row-level Security (RLS): How to apply security measures to limit data access for specific users within the same report.
Bookmarks and Selections: Creating customized views in reports using bookmarks and selection panes.
Power BI AI Features: Leveraging artificial intelligence features in Power BI, such as automated insights, Q&A visuals, and predictive analytics.
Sharing and Collaboration
Publishing to Power BI Service: How to share reports and dashboards on the Power BI cloud platform.
Workspaces and Apps: How to organize and share content with colleagues in a workspace, and how to bundle content into apps.
Embedding Reports: Integrating Power BI reports into other applications like SharePoint or websites.
Collaboration Features: Using Power BI’s commenting and collaboration features for team discussions around reports.
Power BI Dataflows: Using dataflows to manage, transform, and share data in a more reusable and scalable manner.
Power BI Performance and Optimization
Data Model Optimization: Tips for optimizing data models for performance, especially when working with large datasets.
Aggregations: How to aggregate data at different levels to speed up report loading.
Query Folding and Caching: Techniques to optimize data refresh rates and ensure smooth performance.
Power BI Administration and Governance
Power BI Admin Portal: Understanding the settings available for managing user access, usage metrics, and the overall environment.
Governance Best Practices: How to maintain control over content, data sources, and who has access to what.
Training Formats
Beginner to Advanced Levels: Training is often structured into different levels based on experience.
Beginner: Focus on basic functionality like importing data, creating basic visualizations, and generating simple reports.
Intermediate: Covers data modeling, more complex visualizations, and using DAX for custom calculations.
Advanced: Dives deep into DAX, advanced Power Query transformations, and performance optimization.
Instructor-Led Training vs. Self-Paced Learning:
Instructor-Led: Real-time support, hands-on exercises, and direct interaction with experts.
Self-Paced: Online tutorials, videos, and guides that allow you to learn at your own speed.
Certifications: Power BI offers certifications like the Microsoft Certified: Data Analyst Associate exam, which is a great way to validate your skills.
Best Practices and Tips
Simplicity Over Complexity: Keep reports simple and easy to understand for end- users.
Storytelling with Data: Use visuals to tell a compelling story that communicates insights clearly.
Consistency in Reporting: Standardize formatting, layout, and terminology across all reports.
Data Integrity: Always ensure that the data used in reports is accurate and up-to-date.
Key Benefits of Power BI Training
Empowered Decision Making: Users can independently explore data, spot trends, and make informed decisions faster.
Increased Productivity: With interactive dashboards and real-time reporting, teams spend less time manually compiling data and more time analyzing it.
Scalability and Flexibility: Power BI’s ease of use and scalability means that organizations of all sizes can leverage it, from small teams to large enterprises.
Collaboration: Power BI fosters collaboration by enabling easy sharing and co- authoring of reports and dashboards.