Course Program Overview
DP-750 Implementing Data Engineering Solutions Using Azure Databricks
- Duration: 5 Months (Intensive)
- Format: Live Online / Corporate / Blended Learning
- Sessions: 4 per week
- Session Length: 1.5 Hours per session
- Tech Stack: Azure Databricks, Apache Spark, Unity Catalog, Delta Lake, Python (PySpark), SQL, Azure Data Factory, Microsoft Entra ID, Azure Key Vault, Databricks Asset Bundles (DABs), Lakeflow Connect.
- Outcome: Microsoft Certified: Azure Databricks Data Engineer Associate + Production-Ready Project Portfolio.
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đź“Ś Key Exam Information
Certification Name
Microsoft Certified: Azure Databricks Data Engineer Associate
Exam Code
DP-750 (Beta launched March 2026; GA May 2026)
Level
Intermediate (Requires hands-on experience with Spark and Azure ecosystem)
Audience
Data engineers, cloud architects, and MLOps professionals specializing in high-scale data processing on the Databricks Lakehouse Platform.
Exam Format
Case studies, multiple-choice, and "build-list" (drag-and-drop) interactive tasks.
Number of Questions
45–55 Questions
Duration
100 minutes (plus 20 minutes for setup)
Passing Score
700 out of 1000
Delivery
Pearson VUE Online Proctored or Authorized Testing Centers.
Completed
🎯 Who Should Take DP-750
- Data Engineers & Developers: Professionals building ETL/ELT pipelines who want to specialize in the Azure Databricks environment rather than Microsoft Fabric (DP-700).
- Legacy Cert Holders: Those transitioning from the retired DP-203 or the retiring DP-100 (Data Scientist) who need to master MLOps and production-grade Spark workloads.
- Cloud Architects: Architects designing secure, governed lakehouse architectures using Unity Catalog.
- Data Analysts Scaling Up: Analysts moving from traditional SQL to big data processing using Spark SQL and Delta Lake.
🧠Exam Domains & Weightage
The DP-750 exam is structured around the core pillars of the Databricks Lakehouse architecture. Our curriculum is weighted to mirror these exact proportions:
25–30%
Data Exploration and Preparation
Focuses on exploring data using Spark SQL and DataFrames, handling complex data types (nested JSON/Avro), and implementing data cleaning strategies using PySpark.
30–35%
Data Processing and Transformation
The core of the exam. Covers Batch and Stream processing (Structured Streaming), Delta Lake optimization (Z-Order, Liquid Clustering), and advanced ETL patterns using Delta Live Tables (DLT).
20–25%
Data Governance and Security
Deep dive into Unity Catalog. Managing schemas, catalogs, and fine-grained access control (row/column-level security), and auditing data lineage.
15–20%
Operationalizing Data Pipelines
Covers CI/CD for Databricks, monitoring job performance, utilizing Databricks Asset Bundles (DABs), and integrating with Azure DevOps/GitHub.
🏆 Benefits of DP-750 Certification
- Pioneer the Fabric Era: Get certified in Microsoft’s flagship 2026 data platform, making you the first choice for companies migrating to unified cloud analytics.
- Unified Skillset Mastery: Validates your ability to work across Spark, SQL, and Power BI within a single environment (OneLake), removing the need for fragmented data tools.
- High-Demand Career Path: Analytics Engineering is one of the fastest-growing roles in 2026, often commanding salaries in the 40 LPA+ range for certified experts.
- Enhanced Market Visibility: Earn a digital badge that showcases your proficiency in Generative AI and Microsoft Copilot to recruiters and hiring managers worldwide.
🌟 Top 5 Reasons to Choose Adian Soft Solutions for this course
Specialized Databricks Deep-Dive
Unlike generalist data courses, our DP-750 program focuses exclusively on the Databricks ecosystem. We move beyond basic SQL to master advanced PySpark optimization and the Lakehouse architecture, ensuring you become a subject matter expert in high-demand niche technologies.
Unity Catalog & Governance Mastery
Security is the #1 priority for enterprises in 2026. We provide dedicated modules on Unity Catalog—Microsoft’s preferred governance tool for Databricks—teaching you how to implement enterprise-grade security and data discovery that most other programs overlook.
Zero-to-Production CI/CD Focus
Employers don't just want coders; they want engineers who can deploy. Our course includes hands-on training with Databricks Asset Bundles (DABs) and Lakeflow Connect, teaching you to automate deployments just like they are done in top-tier tech firms.
Hybrid-Cloud Portfolio Development
You won't just work in a sandbox. You will build a multi-stage project that integrates Azure Data Factory with Databricks and Power BI. This end-to-end "Lakehouse Portfolio" demonstrates your ability to bridge the gap between raw data and business intelligence.
Exclusive Beta-Exam Insights
As DP-750 is the newest addition to the Azure stable, we provide unique practice labs based on the latest 2026 exam patterns. Our "Exam Simulation" mode mirrors the actual Pearson VUE interface, reducing exam anxiety and boosting first-time pass rates.
Skills You Will Get
Through this course, you will evolve into a specialized Azure Databricks Data Engineer, mastering the lifecycle of big data within a Lakehouse architecture. You will gain hands-on experience in building scalable Medallion Architectures (Bronze, Silver, Gold) and automating complex ETL workflows using Delta Live Tables (DLT). By mastering Unity Catalog, you will develop the ability to enforce enterprise-grade security and data lineage. Finally, you will bridge the gap between development and production by implementing robust CI/CD pipelines and monitoring strategies, ensuring you are prepared to lead high-impact data projects in any enterprise environment.
Apache Spark Mastery
Apache Spark Mastery
Medallion Architecture
Medallion Architecture
Delta Lake & Optimization
Delta Lake & Optimization
Advanced Streaming
Advanced Streaming
Unity Catalog Governance
Unity Catalog Governance
Automated Data Pipelines
Automated Data Pipelines
Databricks Asset Bundles (DABs)
Databricks Asset Bundles (DABs)
Computer Vision
Computer Vision
Course Program
(5 Months)
Classroom / Live Online
120+ Hours
This five month DP 750 program is designed to transform learners into production ready Databricks professionals. By extending the roadmap, each domain is explored in greater depth, with additional labs and case studies to ensure mastery. The journey begins with Spark and Delta Lake foundations, progresses into Medallion architecture and streaming, then governance and security, followed by CI/CD and operationalization, and finally culminates in a comprehensive Capstone Project.
â—Ź Month 1
Exam Coverage: 20–25%
Apache Spark Foundations & Data Exploration
Learners begin by mastering the fundamentals of Apache Spark within Azure Databricks. We cover Spark architecture, RDDs, DataFrames, and Spark SQL, moving from basic queries to complex transformations. A major emphasis is placed on handling diverse data formats such as JSON, Avro, and Parquet. Students learn to clean and prepare datasets using PySpark, ensuring readiness for downstream processing.
Practical Labs:
Provision Databricks workspaces, run Spark SQL queries, and implement PySpark transformations for nested JSON datasets.
Case Studies:
Retail companies analyzing customer transaction logs using Spark SQL for real time insights.
â—Ź Month 2
Exam Coverage: 20–25%
Delta Lake & Medallion Architecture
This month focuses on Delta Lake and the Medallion architecture (Bronze, Silver, Gold). Learners explore ACID transactions, schema enforcement, and advanced features like Time Travel, Z Ordering, and Liquid Clustering. Students design pipelines that move data from raw ingestion (Bronze) to curated (Silver) and business ready (Gold).
Practical Labs:
Build a multi layer Delta Lake pipeline, implement schema evolution, and optimize queries with Z Ordering.
Case Studies:
Financial institutions using Delta Lake to ensure compliance and auditability of transaction records.
â—Ź Month 3
Exam Coverage: 20–25%
Streaming & Real Time Data Processing
Learners advance into Structured Streaming, mastering batch and stream processing. We cover Auto Loader for incremental ingestion and Delta Live Tables (DLT) for automated ETL workflows. Students build real time pipelines that integrate live data feeds into the Lakehouse.
Practical Labs:
Implement a clickstream ingestion pipeline with Structured Streaming, configure Auto Loader for incremental updates, and build DLT workflows.
Case Studies:
Social media platforms processing millions of live events per second for recommendation engines.
â—Ź Month 4
Exam Coverage: 20–25%
Unity Catalog Governance & Security
This month emphasizes governance and security. Learners master Unity Catalog, managing schemas, catalogs, and fine grained access control. We cover row level and column level security, auditing, and lineage tracking. Students learn how to design secure, governed architectures that meet enterprise compliance standards.
Practical Labs:
Configure Unity Catalog permissions, implement row level security, and audit lineage across multiple departments.
Case Studies:
Healthcare providers implementing GDPR compliant data masking strategies using Unity Catalog.
â—Ź Month 5
Exam Coverage: 20–25% + Consolidation of 100% CI/CD
Operationalization & Capstone Project
The final month focuses on operationalizing Databricks solutions. Learners use Databricks Asset Bundles (DABs) for version control and automated deployments, integrate with Azure DevOps/GitHub, and monitor job performance. The program concludes with a Capstone Project, where students design an end to end Lakehouse solution integrating batch, streaming, governance, and BI readiness.
Practical Labs:
Build CI/CD pipelines with DABs, monitor job performance, and deploy automated workflows with Lakeflow Connect.
Case Studies:
Global logistics firms operationalizing data pipelines for real time shipment tracking.
Capstone Project:
Design a global enterprise Lakehouse integrating raw ingestion, streaming, governance, and BI dashboards, serving as a portfolio ready production system.
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-750 Implementing Data Engineering Solutions Using Azure Databricks
DP-750 is the premier 2026 certification for data professionals specializing in the Azure Databricks Lakehouse Platform. It focuses on using Spark, Delta Lake, and Unity Catalog to build scalable, governed data solutions.
DP-203 retired in March 2025. This course is the modern successor for those wanting to specialize in Databricks. If you hold a DP-203, this course is the perfect "up-skill" to stay relevant in a Fabric and Databricks-dominated market.
While basic SQL knowledge is helpful, our course includes a "Python for Spark" bootcamp in Month 1 to ensure you are comfortable writing PySpark code for data transformations.
Unity Catalog is the unified governance layer for Databricks. It is a major focus of the DP-750 exam because it handles all security, auditing, and lineage—skills that are mandatory for enterprise-level roles.
It is the industry-standard way to organize data in a Lakehouse: Bronze (raw), Silver (filtered/cleaned), and Gold (business-ready). You will build a full project using this framework.
The course fee covers training, labs, and exam prep. While we provide assistance with exam registration and occasional vouchers, the official Microsoft exam fee is typically paid directly to Pearson VUE.
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