Course Program Overview
DP 900 Microsoft Azure Data Fundamentals
- Duration: 3 Months
- Format: Live Online / Classroom / Blended / Corporate
- Sessions: 5 per week
- Session Length: 01 Hour of each session
- Tech Stack: Azure SQL Database, Azure Database for PostgreSQL, Azure Database for MySQL, Azure Cosmos DB, Azure Blob Storage, Azure Table Storage, Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, Azure Stream Analytics, Power BI, Azure Purview.
- Outcome: Industry grade portfolio + Microsoft Certification + Career acceleration
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Our placement Record
đź“Ś Key Exam Information
Certification Name
Microsoft Certified: Azure Data Fundamentals
Exam Code
DP 900
Level
Beginner (entry level, no prior technical experience required)
Audience
Business stakeholders, students, or professionals beginning with cloud data concepts and Azure services.
Exam Format
Multiple choice, drag and drop, and scenario based performance tasks.
Number of Questions
Approximately 40–60
Duration
60 minutes (plus 30 minutes for setup and surveys)
Passing Score
700 out of 1000
Delivery
Online proctored or at authorized test centers
Languages Available
English, Japanese, Korean, Simplified Chinese, Spanish, German, French, Portuguese
🎯 Who Should Take DP 900
- Students & Career Starters – University students, fresh graduates, or early career professionals exploring data related roles such as data analyst, BI developer, or cloud associate.
- IT Professionals Expanding Skills – System administrators, developers, or IT staff who want to broaden their knowledge into Azure’s data ecosystem.
- Aspiring Data Professionals – Anyone planning to pursue advanced certifications such as DP 203 (Data Engineering), DP 500 (Analytics Solutions), or even AI focused paths like AI 901.
🧠Exam Domains & Weightage
15–20%
Describe Core Data Concepts
Understand structured, semi structured, and unstructured data, transactional vs. analytical workloads, and the principles of data processing.
25–30%
Describe Relational Data on Azure
Learn schemas, tables, relationships, normalization, and SQL query fundamentals using Azure SQL Database, PostgreSQL, and MySQL.
25–30%
Describe Non Relational Data on Azure
Explore NoSQL databases, JSON document storage, and globally distributed applications with Azure Cosmos DB, Blob Storage, and Table Storage.
25–30%
Describe Analytics Workloads on Azure
Master Synapse Analytics, Data Factory, Data Lake, Stream Analytics, and Power BI for large scale analytics and visualization.
🏆 Benefits of DP 900 Certification
- Global Recognition: Microsoft credentials are respected worldwide.
- Strong Foundation in Data Concepts: Builds essential knowledge of relational, non relational, and analytics workloads, making it easier to progress to advanced certifications.
- Career Advancement: Enhances employability for entry level roles like data analyst, database administrator, or cloud data associate.
- Industry Validation: Confirms your ability to design, query, and visualize data using Azure services.
🌟 Top 5 Reasons to Choose Adian Solutions for this course
Comprehensive Exam Alignment
Our 3 month roadmap is mapped directly to Microsoft’s official DP 900 exam blueprint. Every domain, every skill, and every percentage weightage is covered in detail.
Certification Guarantee & Retake Support
If you don’t pass on your first attempt, we provide extended access and personalized retake support at no extra cost.
Hands On Real World Learning
You’ll actively use Azure SQL Database, Cosmos DB, and Synapse Analytics to design and query datasets, gaining practical exposure to enterprise workloads.
Capstone Project & Portfolio Development
Build an end to end data pipeline integrating ingestion, transformation, and visualization with Power BI. This becomes a professional portfolio piece.
Career & Placement Support
Resume workshops, LinkedIn optimization, mock interviews, and direct placement pathways ensure your certification translates into tangible career outcomes.
Skills You Will Get
By completing the DP 900 Microsoft Azure Data Fundamentals program, you will gain a strong foundation in modern data concepts and Azure services. These skills prepare you for advanced certifications and real world roles in data engineering, analytics, and business intelligence.
Core Data Concepts
Core Data Concepts
Relational Database Skills
Relational Database Skills
Non Relational Data Mastery
Non Relational Data Mastery
Data Integration
Data Integration
Analytics Workloads
Analytics Workloads
Data Visualization
Data Visualization
Data Governance & Compliance
Data Governance & Compliance
End to End Data Pipeline Deployment
End to End Data Pipeline Deployment
Course Program
(3 Months)
Classroom / Live Online
80+ Hours
This three month DP 900 program begins with a deep dive into core data concepts, teaching learners how to differentiate structured, semi structured, and unstructured data while mastering transactional and analytical workloads through relational databases like Azure SQL Database, PostgreSQL, and MySQL. In the second month, the focus shifts to non relational data solutions such as Cosmos DB, Blob Storage, and Table Storage, alongside analytics workloads with Synapse Analytics, Data Lake, and Data Factory to process and analyze large datasets. The final month emphasizes advanced analytics and visualization, where students build real time dashboards with Stream Analytics and Power BI, and apply governance principles using Azure Purview. The program culminates in a capstone project that integrates ingestion, transformation, storage, and visualization into a portfolio ready solution, ensuring complete coverage of DP 900 exam objectives and career ready skills.
â—Ź Month 1
Exam Coverage: 25–35%
Core Data Concepts & Relational Data
Learners establish a strong foundation in data fundamentals by exploring structured, semi structured, and unstructured data, as well as transactional versus analytical workloads. They study relational database design, schemas, tables, relationships, and normalization techniques. Students gain exposure to Azure SQL Database, PostgreSQL, and MySQL, learning how these services are provisioned, scaled, and secured in the cloud. The month emphasizes query writing, covering SELECT statements, filtering, joins, aggregations, and constraints to prepare learners for practical problem solving.
Practical Labs:
Create and query tables in Azure SQL Database, deploy a sample relational database, and practice SQL operations such as joins, aggregations, and constraints.
Case Studies:
Retail company managing customer orders with relational databases; banking system handling transactional workloads securely.
â—Ź Month 2
Exam Coverage: 35–40%
Non Relational Data & Analytics Workloads
Learners explore non relational databases, focusing on flexible data models and modern storage solutions. They study Azure Cosmos DB for globally distributed applications, Blob Storage for unstructured data, and Table Storage for key value scenarios. The curriculum then transitions into analytics workloads, covering Synapse Analytics for large scale queries, Data Lake for big data storage, and Data Factory for ETL pipelines. This month emphasizes batch vs. streaming data, scalability, and enterprise use cases.
Practical Labs:
Create Cosmos DB containers, insert JSON documents, store and query unstructured data in Blob Storage, and build ETL pipelines using Data Factory.
Case Studies:
Social media platforms storing user activity logs in Cosmos DB; e commerce companies analyzing clickstream data with Synapse Analytics.
â—Ź Month 3
Exam Coverage: 30–35% + Consolidation of 100%Â
Advanced Analytics, Visualization & Capstone Project
Learners advance into real time analytics and visualization, working with Azure Stream Analytics to process live data streams and Synapse pipelines for batch analytics. They build dashboards with Power BI, transforming raw datasets into meaningful insights. Governance and compliance are introduced through Azure Purview, teaching students how to classify, secure, and monitor data responsibly. The capstone project consolidates all skills, requiring learners to design an end to end data solution that demonstrates readiness for real world roles.
Practical Labs:
Build real time dashboards with Stream Analytics and Power BI, create batch analytics pipelines with Synapse, and implement governance using Purview.
Case Studies:
Healthcare providers analyzing patient data securely with Purview; logistics companies using Power BI dashboards for fleet management.
Capstone Project:
Design an end to end data solution integrating ingestion with Data Factory, storage in Data Lake, transformation with Synapse, and visualization in Power BI.
Real Roles. Real Results.
Explore Your Post-Course Career
After completing the course, learners can unlock high-impact roles such as Machine Learning Engineer, Cloud Solutions Architect, Data Scientist, and AI Product Lead—across sectors like technology, BFSI, healthcare, retail, and manufacturing.
Machine Learning Engineer
Designs, trains, and optimizes ML models for prediction, classification, and automation across industries like finance, healthcare, and manufacturing.
Data Scientist
Extracts insights from structured and unstructured data using statistical analysis, visualization, and modeling techniques. Drives decision-making and business intelligence.
AI Solutions Architect
Leads the design and deployment of scalable AI systems using cloud platforms, MLOps pipelines, and enterprise-grade frameworks
Deep Learning Researcher
Specializes in neural networks, CNNs, RNNs, GANs, and transformers. Builds models for image recognition, NLP, and generative tasks.
MLOps Engineer
Implements CI/CD pipelines, containerization, and cloud-native deployment for AI models. Ensures reliability, scalability, and performance monitoring.
Generative AI Developer
Builds intelligent applications using LangChain, Hugging Face, and LLMs. Applies RAG pipelines and transformer models to domains like legal tech and marketing.
Computer Vision Engineer
Develops image and video analysis systems using OpenCV, TensorFlow, and deep learning. Works on facial recognition, object detection, and OCR.
NLP Engineer
Creates language models and conversational AI systems using NLTK, SpaCy, and transformers. Powers chatbots, sentiment analysis, and document summarization.
AI Product Lead
Bridges technical teams and business strategy. Oversees AI product lifecycle—from ideation to deployment—ensuring alignment with market needs and ethical standards.
Frequently Asked Questions
DP 900 Microsoft Azure Data Fundamentals
The DP 900 certification is Microsoft’s foundational credential for data literacy in the cloud. It covers core concepts of structured and unstructured data, relational and non relational workloads, and analytics solutions on Azure. Learners gain practical knowledge of SQL databases, NoSQL services, and modern analytics tools like Synapse and Power BI.
This course is designed for anyone starting their journey in data and cloud computing. It is ideal for students, business professionals, and IT staff who want to understand how data is stored, processed, and visualized in Azure. No prior technical experience is required, making it accessible to both technical and non technical backgrounds.
No. DP 900 is a beginner level certification. While basic computer literacy is helpful, the course teaches all concepts from the ground up, including SQL fundamentals, data modeling, and Azure portal navigation.
You will learn to design relational schemas, write SQL queries, configure Cosmos DB for non relational workloads, build ETL pipelines with Data Factory, and create dashboards with Power BI. By the end of the program, you will be able to deploy end to end data solutions on Azure.
The course is a 3 month intensive program consisting of live sessions, hands on labs, and a final capstone project. Each month focuses on a major domain of the exam: relational data, non relational data, and analytics workloads.
The Adian Solutions curriculum covers 100% of the DP 900 exam objectives. Our syllabus is mapped directly to Microsoft’s official weightage, ensuring complete preparation for the exam.
The capstone project involves building a complete data pipeline. You will integrate ingestion with Data Factory, storage in Data Lake, transformation with Synapse, and visualization in Power BI. This project serves as a professional portfolio piece to showcase your readiness for real world data roles.
Yes. We provide structured career guidance, including resume optimization for data roles, interview preparation, and access to our network of 1,000+ global recruiters.
The exam consists of 40–55 questions, including multiple choice, drag and drop, and scenario based tasks. You have 60 minutes to complete the exam.
Microsoft fundamental certifications like DP 900 do not expire. Once earned, the credential remains valid indefinitely, though learners are encouraged to progress to advanced certifications such as DP 203 or PL 300 to stay current with industry trends.
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