How to Pass Microsoft’s Azure Data Engineer Certification – DP-203 Exam Guide
Microsoft Azure offers a comprehensive solution for data engineering through its DP-203 certification, which validates your proficiency in designing and implementing data solutions.
In this comprehensive blog post, we embark on a journey into the world of DP-203 certification, exploring its significance, key topics, preparation strategies, and the invaluable skills it imparts to aspiring data engineers.
What is Data Engineering ?
Data engineering refers to the practice of designing, building, and managing data solutions. It encompasses a wide range of activities aimed at efficiently processing, storing, and analyzing data to extract valuable insights and drive informed decision-making.
5 Important Data Engineering Concepts in Microsoft Azure
Key components of Azure data engineering include:
- Data Ingestion: Capturing and importing data from various sources such as databases, files, streaming platforms, and IoT devices into Azure.
- Data Transformation: Cleaning, enriching, and transforming raw data into a usable format for analysis and reporting.
- Data Storage: Storing and managing data in Azure’s versatile storage solutions, including Azure Data Lake Storage, Azure Blob Storage, and Azure SQL Database.
- Data Processing: Using tools like Azure Databricks, Azure HDInsight, and Azure Synapse Analytics (formerly SQL Data Warehouse) to process and analyze large volumes of data.
- Data Integration: Integrating data from disparate sources to create a unified view for analysis, often involving tools like Azure Data Factory.
- Data Orchestration: Orchestrating and automating data workflows, ETL (Extract, Transform, Load) processes, and data movement between different components.
- Data Warehousing: Designing and managing data warehouses for structured data storage, querying, and reporting using services like Azure Synapse Analytics.
- Streaming Analytics: Processing and analyzing real-time data streams for immediate insights and actions using services like Azure Stream Analytics.
- Machine Learning and AI: Integrating machine learning and artificial intelligence capabilities to derive predictive and prescriptive insights from data.
- Data Governance and Security: Implementing security measures, access controls, and data governance policies to ensure data privacy, compliance, and quality.
Why Azure Data Engineering Associate Certification Exam (DP-203)?
Data Engineering on Microsoft Azure certification exam (DP-203) has gained significant demand due to the growing importance of data engineering in the modern digital landscape. Microsoft Azure’s prominence as a leading cloud platform has contributed to the increasing interest in this certification.
- Rise of Data-Driven Decision-Making
- Digital Transformation
- Azure’s Growing Adoption
- Big Data and Analytics
- Machine Learning and AI
- Data Compliance and Governance
- Cloud Migration
- Real-Time Data Processing
- Career Advancement
What is the DP-203 Certification Exam?
The DP-203 exam assesses your skills and knowledge in designing and implementing data solutions using various Azure data services and technologies. Passing the DP-203 exam demonstrates your proficiency in data engineering concepts and your ability to work with data on the Microsoft Azure cloud platform.
The skills are divided into these functional components-
- Design and implement data storage (15–20%)
- Develop data processing (40–45%)
- Secure, monitor, and optimize data storage and data processing (30–35%)
As per PayScale Report of year 2023, Data Engineers make an average of $95,517 and swinging as high as $135,000 per year.
How to Prepare for Microsoft Data Engineering Associate DP-203 Certification Exam?
First of All Download the Microsoft study guide for DP-203 exam and go through with the topics and functional groups.
- Know Structure of the DP-203 Exam
- Start the Learning Process
- Try Your Hands Labs on Practically with Azure Data Engineering Tools
- Leverage the Microsoft Free Resources
- Must Solve KloudSaga Practice Tests or Udemy Practice Tests!!!
- Get support from Study Groups and join Community.
- Take Time for Rest and Revision
Microsoft Data Engineering Associate Exam Summary:
Exam Name: DP-203: Data Engineering on Microsoft Azure
Exam Code: DP-203
Cost: $165 USD*
Duration: 120 Minutes
Number of Questions: 45–60
Passing Score Required: 700/1000
Schedule Exam: Pearson VUE
Practice Tests: https://courses.kloudsaga.com/courses/microsoft-azure-data-engineer-exam-practice-sets
For 20% OFF Use CouponCode: SUMMER2024
The Data Engineering on Microsoft Azure Certification (DP-203): A Brief Overview:
1. Get started with data engineering on Azure:
The data engineer will often work with multiple types of data like structured, semi-structured, unstructured data to perform many operations as per requirement.
Data lakes are a core element of data analytics architectures. Azure Data Lake Storage Gen2 provides a scalable, secure, cloud-based solution for data lake storage.
Azure Synapse Analytics — a cloud-based platform for big data processing and analysis. It provides a cloud platform for all of these analytical workloads through support for multiple data storage, processing, and analysis technologies in a single, integrated solution. Study Material Link
2. Build data analytics solutions using Azure Synapse serverless SQL pools :
If you are having large amount of data to analyze then Azure Synapse Analytics enables you to apply the SQL skills you use in a relational database to files in a data lake.
By Leveraging a serverless SQL pool in Azure Synapse Analytics, you can use the SQL language to transform data in files in a data lake.
Learn and Practice Securing data and manage users in Azure Synapse serverless SQL pools. Study Material Link
3. Perform data engineering with Azure Synapse Apache Spark Pools:
You need to understand Analyse, Visualize and transform data using Apache Spark pools in Azure Synapse Analytics.
Delta Lake is an open-source storage layer for Spark that enables relational database capabilities for batch and streaming data. By using Delta Lake, you can implement a data lakehouse architecture in Spark to support SQL_based data manipulation semantics with support for transactions and schema enforcement. Study Material Link
4. Work with Data Warehouses using Azure Synapse Analytics:
Learn Load, Analyze & optimize, Manage & monitor and implementing security data warehouse activities in Azure Synapse Analytics. Study Material Link
5. Transfer and transform data with Azure Synapse Analytics pipelines:
Azure Synapse Analytics enables data integration through the use of pipelines, which you can use to automate and orchestrate data transfer and transformation activities. Study Material Link
6. Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics
Hybrid Transactional and Analytical Processing (HTAP) is a technique for near real time analytics without a complex ETL solution. In Azure Synapse Analytics, HTAP is supported through Azure Synapse Link. Study Material Link
7. Data engineering with Azure Databricks
Learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud. Study Material Link
8. Implement a Data Streaming Solution with Azure Stream Analytics
Stream processing enables you to capture and analyze data in real-time. Azure Stream Analytics is a cloud-based stream processing engine that you can use to build highly scalable real-time analytics solutions. Study Material Link
Conclusion:
These given topics will help you to succeed in the Data Engineering journey. KloudSaga Practice Tests cover all the relevant topics with 100% syllabus and question types that you can expect from the real exam. You can pass your DP-203 certification exam on the first attempt.
Thanks for reading my article, I would appreciate your response at support@kloudsaga.com
Our Udemy Visit- https://www.udemy.com/user/kloudsagatutorials/
Udemy Vs KloudSaga Practice Sets- https://kloudsaga.com/udemy-vs-kloudsaga
Happy Learning!
