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Why Practice Tests?
You will easily learn Data Engineering on Azure & most importantly PASS the exam. Let's get the best of the course by attempting practice tests more and more and build confidence.
Though the syllabus is vast and preparation is intense, Microsoft comes with different format of questions like hotspots, use cases, multiple choice, drag and drop, multiple selection and many more. the duration of the exam is around 100 minutes and need to answer around 40-52 questions in the stipulated time. we need to have a thorough practice of the formats and the questions that we can expect in the exam.
These practice tests give you a first hand experience of the real exam and will train you with questions and answers and explanation with why we consider specific option(s) for a question to solve the business problem.
This exam is aimed at engineers who want to validate their skills. Candidates should have knowledge of data processing languages and they should be able to understand parallel processing and data architecture patterns.
They should be able to build and maintain secure and compliant data processing pipelines by using different tools. They should also ensure the efficiency, organization and reliability of data pipelines and data stores given business requirements and constraints.
These practices tests contains 200 questions and covers the following objectives:
1. Design and implement data storage
2. Design and develop data processing
3. Design and implement data security
4. Monitor and optimize data storage and data processing
These practice tests will provide -
1. Online performance-based simulations give hands on work environment experience
2. Questions are similar to exam questions so you test your knowledge of exam objectives
3. Detailed explanations for both correct and distractor answers reinforce the material
4. Study Mode covers all objectives ensuring topics are covered
5. Certification Mode (timed) prepares students for exam taking conditions
What exam does these practice tests cover?
DP-203 Data Engineering on Azure : Data Engineering on Azure covers wide range of topics. Being a data engineer you will be working on identifying data sources, ingestion of data from various sources at different latencies (batch, streams, Near real time and real time), process data, store data in different formats (SQL, Data Lake), build analytics and many more.
Azure data engineers help stakeholders understand the data through exploration, and they build and maintain secure and compliant data processing pipelines by using different tools and techniques. These professionals use various Azure data services and frameworks to store and produce cleansed and enhanced datasets for analysis. This data store can be designed with different architecture patterns based on business requirements, including modern data warehouse (MDW), big data, or Lakehouse architecture.
Azure data engineers also help to ensure that the operationalization of data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. These professionals help to identify and troubleshoot operational and data quality issues. They also design, implement, monitor, and optimize data platforms to meet the data pipelines.
What syllabus does these practice tests cover?
Data Engineering on Azure has the following concepts -
1. Data Storage
Azure Synapse analytics
Azure Cosmos DB
Azure Data Lake Storage Gen 2
Microsoft Purview Data Catalog
SQL Serverless and Spark clusters
Data formats like CSV, Parquet, JSON, Avro
2. Data processing
Azure Synapse pipelines
Azure Data Factory
Azure Stream analytics
Batch Management & pipelines
3. Data Security
Encryption of Data @ rest and in transit
row level security & column level Security
resource tokens & endpoints
4. Monitoring & Troubleshooting
monitoring activities (streams, batch, pipelines, queries, scheduling, logs)
troubleshoot data storage and processing
What is the expectation for the exam?
Candidates for this exam should have subject matter expertise integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions.
Azure data engineers help stakeholders understand the data through exploration, and they build and maintain secure and compliant data processing pipelines by using different tools and techniques. These professionals use various Azure data services and languages to store and produce cleansed and enhanced datasets for analysis.
Azure data engineers also help ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. They deal with unanticipated issues swiftly, and they minimize data loss. They also design, implement, monitor, and optimize data platforms to meet the data pipelines needs.
You are at Doorstep of SUCCESS. Embrace It.
The Practice tests will help your learning on the following objectives
1. Design and implement data storage (15-20%)
2. Design and develop data processing (40-45%)
3. Secure, monitor, and optimize data storage and data processing (30–35%)
Srikanth Kappagantula, a Senior Cloud Architect and an accomplished technical leader with over 23+ years of experience in advisory, solution presales, implementation, architecture and training.
Srikanth carries a great passion for education. Certified in multiple cloud domains in Cloud technologies like Microsoft Azure, AWS, Alibaba Cloud, Google Cloud, Terraform in Architecture, Administration, Devops, Automation, Security and Big Data Analytics. Have extensively worked in developing course content, practice questions to empower students (150+) both one on one and teams in learning and succeed in their certifications.
Besides, Srikanth as Senior cloud architect leads and deliver digital transformation, cloud adoption and migration, innovation, automation, analytics and data management for organizations by empowering clients to build and execute their cloud, big data, AI and Devops strategies to achieve real business outcomes.