DP-900: Azure Data Fundamental big data analytics tools big data solutions

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This beginner-level course introduces learners to the core concepts of data management and data services in Microsoft Azure. It is intended for individuals who are new to cloud data solutions and want to build foundational knowledge in relational, non-relational, big data, and analytics concepts.

Learners will gain an understanding of core data principles, including database structures, data storage options, and data processing techniques. They will explore how Microsoft Azure provides modern data services such as Azure SQL Database, Cosmos DB, Azure Synapse Analytics, and more.

The course also covers basic concepts of data security, compliance, and governance in cloud environments, preparing learners to work effectively with cloud-based data solutions.

By the end of the course, students will be able to describe core data concepts, identify key Azure data services, and demonstrate an understanding of fundamental cloud data operations. This training is an excellent starting point for further certifications and careers in data engineering, database administration, and business intelligence.

• Principles of data and databases
• Relational vs. non-relational data
• Types of data workloads: transactional, analytical

• Concepts of relational data
• Azure SQL Database and Azure Database for PostgreSQL
• Basics of querying relational data with SQL

• Introduction to non-relational (NoSQL) data
• Azure Cosmos DB overview
• Key-value, document, graph, and column-family data models

• Data warehousing fundamentals
• Introduction to Azure Synapse Analytics
• Basics of big data and real-time data analytics

• Data access and authentication
• Data encryption and protection strategies
• Regulatory compliance considerations in Azure

• This course is ideal for students, IT beginners, business analysts, and professionals looking to gain a foundational understanding of data concepts in cloud environments.
• It’s also perfect for anyone preparing for the Microsoft Certified: Azure Data Fundamentals (DP-900) exam or planning to move into data-centric cloud careers.

• No technical background required
• A general interest in databases, data storage, and data analytics concepts

This intermediate-level course prepares learners to design, implement, manage, and monitor operational databases on Microsoft Azure. It is intended for database administrators (DBAs) and data management specialists responsible for managing cloud-based and hybrid data environments.

Students will learn how to deploy Azure SQL solutions (both IaaS and PaaS), configure high availability and disaster recovery, implement security measures, automate tasks, and optimize query performance. The course also emphasizes best practices for monitoring databases and ensuring operational efficiency using Azure-native tools.

By the end of the course, learners will be equipped to administer relational databases effectively in a cloud-first world and will be ready to sit for the DP-300: Administering Microsoft Azure SQL Solutions certification exam.

• Overview of Azure database offerings
• Comparing Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure VMs

• Configuring resources and storage
• Deploying Azure SQL Database and Managed Instances
• Database migration strategies

• Authentication and authorization in Azure SQL
• Data encryption: at rest and in transit
• Implementing compliance controls and auditing

• Using Azure Monitor and SQL Insights
• Query performance tuning and optimization
• Indexing strategies and execution plans

• Automation options in Azure: Elastic Jobs, Azure Automation
• Scheduling maintenance activities
• Implementing alerts and notifications

• High availability architectures
• Geo-replication and failover groups
• Backup and restore options in Azure SQL

• Managing SQL Server in Azure VMs
• Configuring hybrid backup and restore solutions
• Understanding Azure Arc-enabled SQL Server

This course is ideal for:

• Database administrators managing cloud or hybrid environments
• Data engineers expanding into cloud database administration
• IT professionals preparing for the Microsoft Certified: Azure Database Administrator Associate certification

• Basic knowledge of database concepts (tables, indexing, relationships)
• Familiarity with SQL Server and T-SQL querying 
• Some experience with Microsoft Azure fundamentals 

This intermediate-level course teaches learners how to write queries using Transact-SQL (T-SQL), the primary query language for Microsoft SQL Server and Azure SQL Database. It is designed for database professionals, data analysts, and developers who need to extract, modify, and work with data using T-SQL.

Learners will gain a strong foundation in querying relational databases, including selecting, filtering, joining, aggregating, and modifying data. They will also explore more advanced topics such as subqueries, set operations, and error handling in T-SQL.

By the end of the course, students will have the practical skills needed to write efficient T-SQL queries for data retrieval and manipulation tasks in both on-premises and cloud-based environments. This course provides essential preparation for roles involving database administration, development, and business intelligence.

• Basics of relational databases and T-SQL
• Understanding the structure of tables, views, and schemas
• Writing simple SELECT statements

• Using WHERE clauses to filter results
• Sorting and limiting results
• Understanding data types and NULL values

• Introduction to JOIN operations (INNER, OUTER, CROSS, SELF joins)
• Working with multiple data sources
• Best practices for multi-table queries

• Using aggregate functions (SUM, AVG, MIN, MAX, COUNT)
• GROUP BY and HAVING clauses
• Subqueries and derived tables

• Inserting, updating, and deleting data
• Using transactions and error handling
• Introduction to data consistency and concurrency

• Common table expressions (CTEs)
• Window functions (OVER, PARTITION BY)
• Using set operators (UNION, INTERSECT, EXCEPT)

• This course is ideal for database professionals, developers, business analysts, and anyone working with SQL Server or Azure SQL Database who wants to deepen their querying skills.
• It’s especially valuable for individuals preparing for more advanced database certifications or roles in data engineering and data analysis.
   

• Basic understanding of relational database concepts (tables, relationships, keys)
• General familiarity with Microsoft Windows and database technologies
  (No deep SQL knowledge is required — this course teaches it!)

This advanced-level course prepares developers and database professionals to design and implement cloud-native applications that leverage Microsoft Azure Cosmos DB — a globally distributed, multi-model NoSQL database service.

Learners will gain deep knowledge of modeling data for Cosmos DB, partitioning strategies, consistency models, and serverless computing. They will also learn how to optimize performance, secure access, and manage scaling operations for mission-critical applications.

By the end of the course, students will be capable of building scalable, highly available applications that take full advantage of Cosmos DB’s capabilities. The course also prepares learners for the DP-420 certification exam and strengthens skills for cloud-native application development.

• Overview of Azure Cosmos DB capabilities
• Supported APIs: Core (SQL), MongoDB, Cassandra, Gremlin, Table
• Key benefits of global distribution and elasticity

• Best practices for data modeling
• Partitioning strategies for scalability
• Selecting the right API for application needs

• Understanding Request Units (RUs) and cost management
• Autoscale vs. manual throughput
• Serverless deployment strategies

• Configuring multi-region writes
• Designing for consistency and high availability
• Failover policies and geo-replication

• Query optimization techniques
• Indexing policies for better performance
• Change feed patterns for real-time processing

• Authentication and authorization with Azure Active Directory
• Data encryption at rest and in transit
• Implementing role-based access control (RBAC)

• Monitoring with Azure Monitor and Application Insights
• Diagnosing performance bottlenecks
• Best practices for operational excellence

This course is ideal for:

• Cloud developers designing distributed, scalable applications
• Database engineers moving into NoSQL and multi-model data solutions
• Professionals preparing for the Microsoft Certified: Azure Cosmos DB Developer Specialty (DP-420)
   

• Experience developing apps in Azure (AZ-204 knowledge level recommended)
• Familiarity with basic database concepts (relational and NoSQL models)
• Understanding of Azure Fundamentals (AZ-900) is helpful

This advanced-level course provides a comprehensive introduction to designing, implementing, and managing cloud-native applications using Azure Cosmos DB for PostgreSQL. This database service combines the familiarity and ecosystem support of PostgreSQL with the distributed, horizontal scalability of Cosmos DB.

Learners will explore how to design scalable data models, distribute data across multiple nodes (sharding), manage high availability and consistency, and optimize query performance. Additionally, they will gain hands-on experience setting up distributed PostgreSQL clusters, working with Citus extension features, and building globally distributed applications.

By the end of the course, learners will be equipped to build high-performance, scalable, globally available PostgreSQL applications on Azure and will be ready to handle real-world cloud-native database challenges.

• Overview of Azure Cosmos DB ecosyste
• Cosmos DB for PostgreSQL architecture and benefit
• Comparison with other Cosmos DB APIs and traditional PostgreSQL

• Distributed vs. single-node PostgreSQL desig
• Sharding data with Citus
• Choosing distribution columns and co-location strategies

• Setting up Azure Cosmos DB for PostgreSQL clusters
• Managing nodes and scaling out
• Best practices for cluster configuration

• Writing efficient queries for distributed tables
• Local vs. distributed joins and transactions
• Indexing strategies for performance optimization

• Security architecture in Cosmos DB for PostgreSQL
• Implementing authentication, authorization, and network security
• Backup, restore, and disaster recovery options

• Using Azure Monitor for PostgreSQL performance
• Interpreting query plans and tuning workloads
• Scaling strategies: elastic scaling and rebalancing shards

This course is ideal for:

• IT support professionals and desktop administrators
• Endpoint and device management specialists
• Anyone preparing for the MD-102 certification and working with Microsoft 365
   

• Solid understanding of PostgreSQL fundamentals (queries, indexes, schema design)
• Basic experience with Azure services and cloud concepts (AZ-900 recommended)
• Familiarity with distributed systems concepts is helpful but not required

This advanced-level course is designed for data professionals, data architects, and BI developers who are responsible for designing, building, and securing enterprise-grade analytics solutions on Microsoft Azure and integrating them with Microsoft Power BI.

Learners will gain expertise in modeling, transforming, and serving data for scalable, secure, and performant analytical solutions. Topics include building enterprise-grade semantic models, integrating with Azure Synapse Analytics, implementing security (both at the data and reporting layers), and optimizing enterprise reporting using Power BI Premium capacities.

By the end of the course, students will be equipped to create comprehensive, efficient, and secure analytics solutions — and will be prepared for the DP-500: Azure Enterprise Data Analyst Associate certification exam.

• Overview of the enterprise analytics landscape
• Role of an Azure enterprise data analys
• Core Azure services for enterprise-scale analytics

• Designing semantic models for enterprise solutions
• Optimizing large datasets and incremental refresh
• Aggregations, perspectives, and row-level security (RLS)

• Querying and combining data from Synapse
• Connecting Power BI to Synapse dedicated and serverless SQL pools
• Using DirectQuery and hybrid models

• Building reusable ETL pipelines using Power BI Dataflows
• Automating data refresh and managing large datasets
• Best practices for data ingestion, transformation, and storage

• Implementing workspace security and governance
• Managing datasets, workspaces, and deployment pipeline
• Monitoring performance and cost with Premium Capacity Metrics
• Using Power BI Premium Gen2 features effectively
   

This course is ideal for:

• Data analysts transitioning into enterprise data roles
• BI developers building scalable solutions for large organizations
• Data architects designing end-to-end Azure and Power BI analytics architectures
• It’s particularly valuable for those preparing for the Azure Enterprise Data Analyst Associate certification.
   

• Experience with Power BI Desktop (report building and DAX basics)
• Familiarity with Azure fundamentals (Azure Synapse, storage solutions helpful)
• Knowledge of basic database concepts and data modeling

This intermediate-level course introduces learners to the concepts, architecture, and tools needed to build a Lakehouse using Microsoft Fabric, Microsoft's unified SaaS solution for data engineering, data integration, and business intelligence.

Students will explore how Microsoft Fabric combines data lakes and data warehouses into a single platform, leveraging technologies like OneLake, Delta Lake tables, and Apache Spark runtimes. The course also covers how to ingest, transform, and manage data efficiently for analytical workloads at enterprise scale.

By the end of the course, learners will understand how to design, implement, and optimize a Lakehouse solution in Microsoft Fabric — a crucial skillset for modern data engineers, data architects, and analytics professionals.

• Overview of Microsoft Fabric architecture
• Key components: OneLake, Dataflows Gen2, Lakehouse, Warehouse, and Notebooks
• Differences between traditional lakes, warehouses, and Lakehouses

• Creating a Lakehouse in Microsoft Fabric
• Working with Delta tables and Spark tables
• Designing efficient data models for a Lakehouse architecture

• Using Dataflows Gen2 to load data into a Lakehouse
• Data transformation with notebooks and Spark
• Best practices for staging and cleaning data

• Organizing data in OneLake
• Security considerations: access control, row-level security
• Versioning, schema evolution, and time travel with Delta tables

• Querying data with SQL Endpoints
• Integrating Lakehouse data with Power BI
• Optimizing queries for performance and cost

• Monitoring dataflows and pipeline performance
• Optimizing Spark job performance
• Debugging and troubleshooting common Lakehouse issues
   

This course is ideal for:

• Data engineers working with cloud data platforms
• Data architects designing modern analytical solutions
• BI developers integrating large-scale data into reporting system
• It’s especially valuable for professionals adopting Microsoft Fabric as part of an organization's modern data estate strategy.
   

• Understanding of core data concepts (DP-900: Azure Data Fundamentals recommended)
• Experience with cloud data services (Azure Synapse, Azure Data Factory helpful)
• Basic knowledge of SQL and/or Spark (preferred but not mandatory)

This intermediate-level course teaches learners how to design, implement, and optimize enterprise-grade data warehouse solutions using Microsoft Fabric.

Students will gain hands-on experience creating and managing dedicated SQL warehouses in Fabric, working with distributed compute, loading and transforming large datasets, modeling data for analytics, and securing and monitoring data warehouses at scale.

The course emphasizes best practices for designing scalable, efficient, and secure data warehouse architectures that integrate seamlessly with Microsoft Fabric's Lakehouse, OneLake, and Power BI environments.

By the end of the course, learners will be prepared to build and manage cloud-native data warehouse solutions that support modern analytics workloads and business intelligence reporting.

• Overview of Microsoft Fabric architecture
• Core components: OneLake, Data Warehouse, Lakehouse
• Positioning data warehousing in the modern analytics ecosystem

• Creating dedicated SQL warehouses in Fabric
• Schema design and data distribution techniques
• Loading structured and semi-structured data

• Using T-SQL and Spark notebooks for transformations
• Building star schemas and dimensional models
• Managing large datasets and incremental loads

• Implementing access control, encryption, and data masking
• Auditing, monitoring, and setting up alerts
• Optimizing performance using indexing, partitioning, and caching

• Building reports and dashboards from warehouse data
• Enabling direct query and import models
• Best practices for visualizing large datasets

This course is ideal for:

• Data engineers managing enterprise data platforms
• Database administrators migrating workloads to the cloud
• Data architects designing large-scale analytics infrastructures
• BI developers optimizing reporting performance
• It’s especially useful for professionals adopting Microsoft Fabric for unified data and analytics solutions.
   

• A solid understanding of database fundamentals (tables, relationships, SQL querying)
• Experience with data modeling for analytics (e.g., star schema design)
• Basic familiarity with Azure or cloud storage concepts is helpful but not mandatory

This intermediate-level course teaches learners how to build and manage real-time analytics solutions using Microsoft Fabric. It focuses on ingesting, processing, and analyzing streaming data to deliver instant insights for dynamic, fast-paced business environments.

Students will learn how to work with Fabric’s event streaming features, create and query KQL (Kusto Query Language) databases, and integrate streaming data with analytics tools like Power BI. The course emphasizes designing scalable architectures for real-time decision-making, applying security best practices, and monitoring system health and performance.

By the end of the course, learners will be equipped to design, implement, and optimize real-time data processing solutions that handle high volumes of data with minimal latency — critical for industries like finance, retail, IoT, and healthcare.

• Overview of Microsoft Fabric’s real-time analytics capabilities
• Use cases and benefits of real-time data solutions
• Core services: Event Streams, KQL databases, and integration points

• Setting up event hubs and streaming data sources
• Building real-time ingestion pipelines
• Processing data with stream analytics patterns

• Introduction to Kusto Query Language (KQL)
• Creating databases and tables for real-time data
• Querying and analyzing streaming datasets

• Connecting streaming data to Power BI dashboards
• Designing real-time reports and alerting systems
• Enabling decision-making through real-time visual insights

• Implementing security controls for streaming data
• Monitoring performance and system health
• Tuning ingestion and query performance for efficiency
  

This course is ideal for:

• Data engineers building real-time data pipelines
• Cloud architects designing event-driven systems
• Data analysts and BI developers creating live dashboards and monitoring systems
• IT professionals modernizing business intelligence and operations with streaming data
   

• Basic understanding of cloud data services and analytics concepts
• Familiarity with database fundamentals (tables, queries)
• Experience with Power BI and/or Azure Synapse Analytics is helpful but not mandatory
• Knowledge of simple scripting or querying languages (like SQL) is a plus

This intermediate-level course prepares learners to become skilled functional consultants who can design, implement, and manage solutions using the full suite of Microsoft Power Platform tools: Power Apps, Power Automate, Power BI, and Power Virtual Agents.

Students will learn how to gather requirements, design solutions, configure apps and flows, and create dashboards and chatbots — all aligned with business needs. The course also covers governance, administration, security, and working with Microsoft Dataverse to build scalable, secure solutions.

By the end of the course, students will be ready to create end-to-end business solutions using the Power Platform and be well-prepared for the PL-200: Microsoft Power Platform Functional Consultant Associate certification exam.

• Understanding the functional consultant’s role
• Overview of Power Platform capabilitie
• Core components: Power Apps, Power Automate, Power BI, Power Virtual Agents, Dataverse

• Data modeling basics: tables, columns, and relationships
• Managing business rules and validation
• Creating and securing Dataverse environments

• Designing canvas apps and model-driven apps
• Creating responsive app interfaces
• Connecting apps to various data sources

• Designing workflows to automate business tasks
• Building cloud flows and business process flows
• Error handling, triggers, and approvals

• Importing and transforming data
• Building and publishing dashboards and reports
• Using Power BI in conjunction with Power Platform apps

• Designing conversational chatbots for customer and internal use
• Integrating bots with flows and apps
• Managing chatbot publishing and lifecycle

• Configuring user roles and security policies
• Managing solutions and environments
• Governance, licensing, and compliance best practices
   

This course is ideal for:

• Functional consultants working with Microsoft Business Applications
• Business analysts building advanced solutions
• Power Platform makers moving toward solution architect or consultant roles
• It’s perfect for those pursuing the Microsoft Power Platform Functional Consultant Associate (PL-200) certification.
   

• A good understanding of business processes and workflows
• Basic hands-on experience with Microsoft Power Platform apps (especially Power Apps and Power Automate)
• Familiarity with Microsoft 365 services is helpful but not mandatory

This intermediate-level course is designed for data professionals and business intelligence (BI) specialists who want to learn how to analyze data, create data models, and deliver actionable business insights using Microsoft Power BI.

Learners will cover the full end-to-end data analysis process: connecting to data sources, transforming and preparing data, building robust data models, creating visualizations, and sharing reports and dashboards. The course also focuses on implementing proper security models and optimizing performance for enterprise-scale solutions.

By the end of the course, learners will be fully prepared to take the PL-300: Microsoft Power BI Data Analyst Associate certification exam and be able to build impactful, enterprise-ready data solutions.

• Overview of the data analysis process
• Understanding the Power BI ecosystem: Desktop, Service, and Mobile
• Key roles and responsibilities of a Power BI Data Analyst

• Connecting to different data sources
• Cleaning, transforming, and loading data with Power Query
• Profiling data and resolving inconsistencies

• Designing and building data models
• Managing relationships and hierarchies
• Implementing DAX (Data Analysis Expressions) for calculations and measures

• Building compelling and effective reports
• Creating dashboards for monitoring KPIs and trends
• Enhancing reports with filters, slicers, and bookmarks

• Performing advanced analytics with Power BI
• Sharing datasets, reports, and dashboards securely
• Using workspaces and apps for collaboration

• Implementing Row-Level Security (RLS)
• Managing Power BI datasets and gateways
• Optimizing performance and managing refresh schedules
   

This course is ideal for:

• Data analysts looking to leverage Power BI for insights
• BI professionals modernizing reporting and analytics solutions
• Business users moving into more technical data roles
• It’s perfect for anyone aiming to become a Microsoft Power BI Data Analyst Associate (PL-300).
   

• Basic knowledge of data concepts (tables, relationships, basic statistics)
• Familiarity with Excel functions or other reporting tools is helpful
• No formal programming or database background required

This advanced-level course is designed for experienced professionals who want to become Solution Architects specializing in the Microsoft Power Platform.

Learners will focus on analyzing business needs, designing secure, scalable solutions, and translating requirements into robust architecture designs using Power Apps, Power Automate, Power BI, Power Virtual Agents, and Microsoft Dataverse.

The course emphasizes governance, security, integration, and application lifecycle management (ALM) to deliver successful, enterprise-grade digital transformation projects.

By the end of the course, students will be fully prepared to function as Power Platform Solution Architects and to sit for the PL-600: Microsoft Power Platform Solution Architect Expert certification exam.

• Understanding the Solution Architect role
• Working with stakeholders and project teams
• Overview of responsibilities: design, governance, risk management

• Designing solution architecture aligned with business requirements
• Assessing current environments and identifying gaps
• Planning integrations and data strategies

• Modeling data with Microsoft Dataverse
• Planning relationships, business rules, and automation
• Designing for scalability, performance, and governance

• Designing model-driven apps, canvas apps, and portals
• Designing scalable cloud flows, desktop flows, and system integrations
• Using Microsoft Azure services to extend solutions

• Implementing security models and policies
• Managing environment strategies and deployment pipelines
• Building ALM strategies for continuous integration and delivery (CI/CD)

• Establishing best practices and standards
• Building a Center of Excellence (CoE) for adoption and governance
• Monitoring usage, performance, and adoption
   

This course is ideal for:

• Experienced functional consultants, developers, or architects
• IT leaders planning to deliver enterprise Power Platform solutions
• Senior professionals aiming to lead complex digital transformation projects
• It’s perfect for candidates seeking the Microsoft Certified: Power Platform Solution Architect Expert (PL-600) credential.
   

• Extensive hands-on experience with Microsoft Power Platform components (Power Apps, Power Automate, Power BI)
• Experience leading solution design and implementation
• Familiarity with Microsoft 365, Dynamics 365, and Azure services is very helpful