Microsoft DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric Practice Exam
Microsoft DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric Practice Exam
About Microsoft DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric Exam
The Microsoft DP-700: Implementing Data Engineering for Analytics Exam evaluates your expertise in designing, implementing, and managing data-driven solutions within a robust analytics framework. The DP-700 exam focuses on critical technical skills essential for managing data pipelines, securing analytics solutions, and ensuring system performance optimization. Candidates preparing for the exam will be able to load, transform, and organize data to support advanced analytics, collaborating closely with analytics engineers, architects, analysts, and administrators to deploy effective data engineering solutions.
Skills Gained
- Data Ingestion and Transformation: Master the ability to extract, load, and transform data using SQL, PySpark, and Kusto Query Language (KQL), making data ready for analysis.
- Securing Analytics Solutions: Develop skills to secure and manage data pipelines and analytics solutions, ensuring data confidentiality and integrity throughout the analytics lifecycle.
- System Monitoring and Optimization: Gain expertise in setting up monitoring systems and optimizing performance within analytics platforms, ensuring data solutions operate smoothly and efficiently.
Who should take the exam?
The Microsoft DP-700 exam is tailored for professionals with a deep understanding of data loading patterns, data architectures, and orchestration processes. If you are responsible for managing the data engineering lifecycle within an analytics framework and have hands-on experience with SQL, PySpark, or KQL, this exam is designed for you.
Key Skills Evaluated
- Data Ingestion and Transformation: Candidates will demonstrate proficiency in importing and reshaping data to align with analytics needs.
- Solution Security and Management: Skills in securing and managing an analytics solution are tested to ensure that data is well-protected and compliant with security standards.
- Analytics Solution Monitoring and Optimization: Candidates are assessed on their ability to monitor and improve the performance of analytics platforms to maintain efficient data workflows.
The DP-700 exam is essential for data engineers, analytics professionals, and technical leads who work directly with analytics engineers, architects, and other stakeholders to deploy impactful data engineering solutions that support business intelligence and analytics goals.
Course Outline
The Microsoft DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric Exam covers the following topics -
Domain 1 - Understand to implement and manage an analytics solution (30–35%)
1.1 Explain and Configure Microsoft Fabric workspace settings
- Learn to configure Spark workspace settings
- Learn to configure domain workspace settings
- Learn to configure OneLake workspace settings
- Learn to cconfigure data workflow workspace settings
1.2 Explain and Implement lifecycle management in Fabric
- Configure version control
- Implement database projects
- Create and configure deployment pipelines
1.3 Explain and Configure security and governance
- Implement workspace-level access controls
- Implement item-level access controls
- Implement row-level, column-level, object-level, and file-level access controls
- Implement dynamic data masking
- Apply sensitivity labels to items
- Endorse items
1.4 Explain the process of Orchestrate
- Choose between a pipeline and a notebook
- Design and implement schedules and event-based triggers
- Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expressions
Domain 2 - Understand to ingest and transform data (30–35%)
2.1 Explain to design and implement loading patterns
- Design and implement full and incremental data loads
- Prepare data for loading into a dimensional model
- Learn to design and implement a loading pattern for streaming data
2.2 Explain to ingest and transform batch data
- Learn to choose an appropriate data store
- Learn to choose between dataflows, notebooks, and T-SQL for data transformation
- Learn to create and manage shortcuts to data
- Learn to implement mirroring
- Learn to ingest data by using pipelines
- Learn to transform data by using PySpark, SQL, and KQL
- Learn about Denormalize data
- Learn about group and aggregate data
- Learn to handle duplicate, missing, and late-arriving data
2.3 Explain to ingest and transform streaming data
- Learn to choose an appropriate streaming engine
- Learn to process data by using eventstreams
- Learn to process data by using Spark structured streaming
- Learn to process data by using KQL
- Learn to create windowing functions
Domain 3 - Understanding to Monitor and optimize an analytics solution (30–35%)
3.1 Explain to Monitor Fabric items
- Learn to monitor data ingestion
- Learn to monitor data transformation
- Learn to monitor semantic model refresh
- Learn to configure alerts
3.2 Explain to identify and resolve errors
- Learn to identify and resolve pipeline errors
- Learn to identify and resolve dataflow errors
- Learn to identify and resolve notebook errors
- Learn to identify and resolve eventhouse errors
- Learn to identify and resolve eventstream errors
- Learn to identify and resolve T-SQL errors
3.2 Explain Optimize performance
- Learn to optimize a lakehouse table
- Learn to optimize a pipeline
- Learn to optimize a data warehouse
- Learn to optimize eventstreams and eventhouses
- Learn to optimize Spark performance
- Learn to optimize query performance
What do we offer?
- Full-Length Mock Test with unique questions in each test set
- Practice objective questions with section-wise scores
- In-depth and exhaustive explanation for every question
- Reliable exam reports evaluating strengths and weaknesses
- Latest Questions with an updated version
- Tips & Tricks to crack the test
- Unlimited access
What are our Practice Exams?
- Practice exams have been designed by professionals and domain experts that simulate real-time exam scenario.
- Practice exam questions have been created on the basis of content outlined in the official documentation.
- Each set in the practice exam contains unique questions built with the intent to provide real-time experience to the candidates as well as gain more confidence during exam preparation.
- Practice exams help to self-evaluate against the exam content and work towards building strength to clear the exam.
- You can also create your own practice exam based on your choice and preference
