- 1. What is the Azure Data Engineer Associate Bootcamp?The Azure Data Engineer Associate Bootcamp by DreamsPlus is an intensive program designed to prepare you for the Microsoft Azure Data Engineer Associate Certification (DP-203). It focuses on building skills in data storage, processing, security, and optimization.
- 2. Who should attend this bootcamp?This program is ideal for:
- Aspiring data engineers aiming to specialize in Azure.
- IT professionals and database administrators transitioning to cloud-based data solutions.
- Those pursuing the DP-203 certification to enhance their career prospects.
- 3. What topics are covered in the course?Key areas include:
- Designing and implementing data storage solutions.
- Developing data processing solutions (batch and streaming).
- Managing data pipelines and Spark jobs.
- Securing, monitoring, and optimizing data storage and processing.
- 4. What are the prerequisites for enrolling?Participants should have:
- Basic understanding of data engineering concepts.
- Familiarity with relational and non-relational data systems.
- Knowledge of Azure fundamentals is recommended but optional.
- 5. How is the course delivered?The bootcamp offers two modes of delivery:
- In-person classes at the DreamsPlus center in Chennai for hands-on, instructor-led training.
- Online sessions with live interactions, designed for learners worldwide.
- 6. Does the program include practical, hands-on training?Yes, the bootcamp emphasizes practical experience. You’ll work on interactive workshops, real-world data engineering scenarios, and use Azure tools like Synapse Analytics, Data Lake, and Databricks.
- 7. How does this bootcamp prepare me for the DP-203 certification exam?The curriculum is aligned with the Microsoft DP-203 Exam syllabus. It provides a blend of theoretical knowledge and practical skills to ensure you are fully prepared for certification and real-world applications.
- 8. What skills will I gain from this course?You’ll learn to:
- Design scalable data storage and partitioning strategies.
- Build and optimize data pipelines for batch and streaming workloads.
- Implement data security and compliance measures.
- Monitor and troubleshoot Azure data solutions.
- 9. Will I receive a certificate after completing the course?Yes, you will receive a DreamsPlus Bootcamp Completion Certificate. The program also equips you to earn the Microsoft Azure Data Engineer Associate Certification (DP-203).
- 10. How can I register or get more information?You can register or inquire by:
- 📞 Phone: +91 95000 56713
- 📧 Email: support@dreamsplus.in Visit dreamsplus.in for more details and registration options!
Azure Cloud
Azure Data Engineer Associate Boot Camp
Master Big Data with Our Azure Data Engineering Course DreamsPlus offers a comprehensive Azure Data Engineer Associate…
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Master Big Data with Our Azure Data Engineering Course
DreamsPlus offers a comprehensive Azure Data Engineer Associate Boot Camp in Chennai and online, designed to provide hands-on experience and prepare you for the Microsoft certification in data engineering.
Design and implement data storage (15–20%)
Implement a partition strategy
- Create a file partition strategy;
- create a partition strategy for analytical workloads;
- create a streaming workload strategy;
- create a partition strategy for Azure Synapse Analytics;
- Determine which instances of Azure Data Lake Storage Gen2 require partitioning.
Design and implement the data exploration layer
- Utilising a computational solution that makes use of Spark cluster and SQL serverless, create and run queries.
- It is recommended to utilise Azure Synapse Analytics database templates and to put them into practice.
- Upload updated or new data lineage to Microsoft Purview.
- Use the Microsoft Purview Data Catalogue to browse and search metadata.
Develop data processing (40–45%)
Ingest and transform data
- Create and apply incremental loads
- The following can be used to transform data
- clean data,
- handle duplicate data,
- handle missing data,
- handle late-arriving data,
- split data,
- shred JSON,
- encode and decode data,
- configure error handling for a transformation,
- transform data using Apache Spark,
- transform data using Transact-SQL (T-SQL), ingest and transform data using
- Azure Synapse Pipelines transform data using Azure Stream Analytics.
Develop a batch processing solution
- Utilise Azure Data Lake Storage,
- Azure Databricks,
- Azure Synapse Analytics,
- Azure Data Factory to create batch processing solutions.
- Data pipelines can be created,
- Resources can be scaled,
- Batch sizes can be specified,
- Jupyter or Python notebooks can be integrated into a data pipeline,
- data can be upserted,
- data can be reverted to a previous state,
- exception handling can be configured,
- batch retention can be configured,
- data can be read from and written to a delta lake.
Develop a stream processing solution
- Use Azure Event Hubs and Stream Analytics to create a stream processing solution.
- Using Spark structured streaming
- process data
- create windowed aggregates
- handle schema drift
- process time series data
- process data across partitions
- process within a single partition
- scale resources
- create tests for data pipelines
- optimise pipelines for analytical or transactional purposes
- manage interruptions; configure exception handling
- upsert data
- replay archived stream data
Manage batches and pipelines
- Manage data pipelines in Azure Data Factory or Azure Synapse Pipelines
- Handle failed batch loads
- Validate batch loads
- Arrange data pipelines using Azure Synapse Pipelines or Data Factory.
- Manage Spark jobs in a pipeline
- Apply version control for pipeline artefacts
Secure, monitor, and optimize data storage and data processing (30–35%)
Implement data security
- Put data masking into practice.
- Implement row-level and column-level security
- enable Azure role-based access control (RBAC)
- create POSIX-like access control lists (ACLs) for Data Lake Storage Gen2
- encrypt data both in transit and at rest
- Establish a strategy for data preservation
- create secure endpoints, both public and private
- add resource tokens to Azure Databricks
- load sensitive data into a Data Frame write encrypted
- data to tables or Parquet files
- handle sensitive data.
Monitor data storage and data processing
- Install the logging that Azure Monitor uses.
- Monitoring service configuration,
- stream processing monitoring,
- data movement performance measurement,
- system-wide data statistics monitoring and updating,
- data pipeline performance monitoring,
- query performance measurement,
- pipeline test scheduling and monitoring,
- Azure interpretation Track logs and metrics Put in place a pipeline alerting plan.
Optimize and troubleshoot data storage and data processing
- Compact tiny files
- Optimise resource management
- manage data skew
- manage data spill
- tune queries using indexers
- tune queries using cache
- Investigate a failed Spark task.
- Investigate a failed pipeline run, encompassing actions carried out in external services
FAQs for Azure Data Engineer Associate Bootcamp
What Will You Learn?
- Acquire the knowledge and skills in data engineering that are necessary for the Azure Data Engineer Associate position.
- Gain an understanding of Azure's architecture and data services to bolster your Microsoft certification.
- Gain expertise in creating and executing data engineering solutions.
- Participate in interactive workshops to acquire practical experience in order to get ready for the Azure Data Engineer Associate certification.
Course Curriculum
Course Benefits
-
Prepare for the Microsoft Azure Data Engineer Associate certification.
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Enhance your data engineering skills for advanced roles.
-
Improve your career prospects with Microsoft certification.
-
Stay ahead in the competitive job market with expertise in Azure Data Engineer Associate roles.
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