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Data Engineering on Microsoft Azure
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4.8 (2096 Ratings)
Data Engineering on Microsoft Azure refers to the process of designing, implementing, and managing data pipelines and workflows on Microsoft’s cloud platform, Azure. It involves the collection, ingestion, transformation, and storage of data to make it ready for analysis, reporting, or machine learning. Azure’s flexibility and scalability make it a popular choice for organizations looking to harness the power of data in the cloud
Overview
The Syllabus
Curriculum Designed by Experts
Design and Implement Data Storage (40-45%)
Design a data storage structure
- design an Azure Data Lake solution
- recommend file types for storage
- recommend file types for analytical queries
- design for efficient querying
- design for data pruning
- design a folder structure that represents the levels of data transformation
- design a distribution strategy
- design a data archiving solution
Design a partition strategy
- design a partition strategy for files
- design a partition strategy for analytical workloads
- design a partition strategy for efficiency/performance
- design a partition strategy for Azure Synapse Analytics
- identify when partitioning is needed in Azure Data Lake Storage Gen2
Design the serving layer
- design star schemas
- design slowly changing dimensions
- design a dimensional hierarchy
- design a solution for temporal data
- design for incremental loading
- design analytical stores
- design metastores in Azure Synapse Analytics and Azure Databricks
Implement physical data storage structures
- implement compression
- implement partitioning
- implement sharding
- implement different table geometries with Azure Synapse Analytics pools
- implement data redundancy
- implement distributions
- implement data archiving
Implement logical data structures
- build a temporal data solution
- build a slowly changing dimension
- build a logical folder structure
- build external tables
- implement file and folder structures for efficient querying and data pruning
Implement the serving layer
- deliver data in a relational star schema
- deliver data in Parquet files
- maintain metadata
- implement a dimensional hierarchy
Design and Develop Data Processing (25-30%)
Ingest and transform data
- transform data by using Apache Spark
- transform data by using Transact-SQL
- transform data by using Data Factory
- transform data by using Azure Synapse Pipelines
- transform data by using Stream Analytics
- cleanse data
- split data
- shred JSON
- encode and decode data
- configure error handling for the transformation
- normalize and denormalize values
- transform data by using Scala
- perform data exploratory analysis
Design and develop a batch processing solution
- develop batch processing solutions by using Data Factory, Data Lake, Spark, Azure Synapse Pipelines, PolyBase, and Azure Databricks
- create data pipelines
- design and implement incremental data loads
- design and develop slowly changing dimensions
- handle security and compliance requirements
- scale resources
- configure the batch size
- design and create tests for data pipelines
- integrate Jupyter/IPython notebooks into a data pipeline
- handle duplicate data
- handle missing data
- handle late-arriving data
- upsert data
- regress to a previous state
- design and configure exception handling
- configure batch retention
- design a batch processing solution
- debug Spark jobs by using the Spark UI
Design and develop a stream processing solution
- develop a stream processing solution by using Stream Analytics, Azure Databricks, and Azure Event Hubs
- process data by using Spark structured streaming
- monitor for performance and functional regressions
- design and create windowed aggregates
- handle schema drift
- process time series data
process across partitions - process within one partition
- configure checkpoints/watermarking during processing
- scale resources
- design and create tests for data pipelines
- optimize pipelines for analytical or transactional purposes
- handle interruptions
- design and configure exception handling
- upsert data
- replay archived stream data
- design a stream processing solution
Manage batches and pipelines
- trigger batches
- handle failed batch loads
- validate batch loads
- manage data pipelines in Data Factory/Synapse Pipelines
- schedule data pipelines in Data Factory/Synapse Pipelines
- implement version control for pipeline artifacts
- manage Spark jobs in a pipeline
Design and Implement Data Security (10-15%)
Design security for data policies and standards
- design data encryption for data at rest and in transit
- design a data auditing strategy
- design a data masking strategy
- design for data privacy
- design a data retention policy
- design to purge data based on business requirements
- design Azure role-based access control (Azure RBAC) and POSIX-like Access Control List(ACL) for Data Lake Storage Gen2
- design row-level and column-level security
Implement data security
- implement data masking
- encrypt data at rest and in motion
- implement row-level and column-level security
- implement Azure RBAC
- implement POSIX-like ACLs for Data Lake Storage Gen2
- implement a data retention policy
- implement a data auditing strategy
- manage identities, keys, and secrets across different data platform technologies
- implement secure endpoints (private and public)
- implement resource tokens in Azure Databricks
- load a DataFrame with sensitive information
- write encrypted data to tables or Parquet files
- manage sensitive information
Monitor and Optimize Data Storage and Data Processing (10-15%)
Monitor data storage and data processing
- implement logging used by Azure Monitor
- configure monitoring services
- measure performance of data movement
- monitor and update statistics about data across a system
- monitor data pipeline performance
- measure query performance
- monitor cluster performance
- understand custom logging options
- schedule and monitor pipeline tests
- interpret Azure Monitor metrics and logs
- interpret a Spark directed acyclic graph (DAG)
Optimize and troubleshoot data storage and data processing
- compact small files
- rewrite user-defined functions (UDFs)
- handle skew in data
- handle data spill
- tune shuffle partitions
- find shuffling in a pipeline
- optimize resource management
- tune queries by using indexers
- tune queries by using cache
- optimize pipelines for analytical or transactional purposes
- optimize pipeline for descriptive versus analytical workloads
- troubleshoot a failed spark job
- troubleshoot a failed pipeline run
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Course completion certificate and Global Certifications are part of our all Master Program
Skills Covered
Like the Curriculum ? Let's Get Started
Why Enroll for Data Engineering on Microsoft Azure ?
In-Demand Skills
Looking to boost your career? Enroll in Data Engineering on Microsoft Azure Course Training. Learn in-demand skills like data storage, processing, and security on Azure. With this certification, you'll have the know-how to create, oversee, and improve scalable data solutions in the cloud.
Career Opportunities
Unlock exciting career opportunities with Data Engineering on Microsoft Azure Course Training. This certification prepares you for roles like Azure Data Engineer, Data Architect, and Analytics Engineer. Gain expertise in building scalable solutions, making you a sought-after professional in the field.
Cloud Adoption
Drive cloud adoption with Data Engineering on Microsoft Azure Course Training. Master essential skills like data integration, storage, and security in Azure’s cloud ecosystem. This certification equips you to harness the power of cloud platforms, enabling seamless data management for scalable business solutions.
Scalability and Flexibility
Boost your career with Data Engineering on Microsoft Azure Course Training.Develop your knowledge of creating adaptable and scalable data solutions.This certification enables you to efficiently manage large datasets,ensuring adaptability and performance,making you a highly valuable asset in the cloud-driven world.
Cost Management
Optimize your cloud spending with Data Engineering on Microsoft Azure Course Training. Learn essential cost management skills to track, allocate, and reduce expenses in Azure environments. This certification helps you efficiently manage resources, making your data solutions more cost-effective and scalable.
Security and Compliance
Learn Data Engineering for Security and Compliance with Microsoft Azure Course Training. This certification equips you with the skills to safeguard data, ensure regulatory compliance, and implement robust security protocols on Azure, making you a key asset in managing secure cloud solutions.
Course benefits
Who Can Apply for Red Hat Linux
- Information Architects and Statisticians
- Developers looking to master Machine Learning and Predictive Analytics
- Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
- Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
- Anyone who wants to learn machine learning, artificial intelligence, data visualization, data analytics, data structures, and algorithms (DSA).
Why Data Engineering on Microsoft Azure?
Scalability
Learn to build scalable data solutions with Data Engineering on Microsoft Azure Course Training. This certification equips you with the expertise to design systems that handle growing data efficiently. Master Azure’s scalability features to ensure seamless performance and reliability in cloud environments.
Flexibility
Gain unmatched flexibility with Data Engineering on Microsoft Azure Course Training. This certification equips you to adapt data solutions as business needs evolve. Master Azure's flexible tools to scale, customize, and optimize data processes, making you a versatile data engineering expert in cloud technology.
Cost-Effectiveness
Maximize cost-effectiveness with Data Engineering on Microsoft Azure Course Training. Learn Data Engineering for Security and Compliance with Microsoft Azure Course Training Learn to leverage Azure’s pricing models and tools to build efficient, scalable solutions without overspending.
Security and Compliance
Learn Data Engineering for Security and Compliance with Microsoft Azure Course Training This certification teaches you to secure data, enforce compliance with industry regulations, and build robust, scalable systems on Azure. Gain the skills to protect sensitive data and ensure regulatory adherence across cloud environments.
Hybrid Capabilities
Unlock hybrid capabilities with Data Engineering on Microsoft Azure Course Training. This certification helps you seamlessly integrate on-premise and cloud data solutions. Gain expertise in Azure’s hybrid tools, ensuring flexibility and connectivity across diverse environments for optimal data management.
Innovation
Drive innovation with Data Engineering on Microsoft Azure Course Training. This certification empowers you to leverage cutting-edge Azure tools for data management, analytics, and AI. Stay ahead in the field by mastering innovative solutions that enhance data efficiency, scalability, and business insights on Azure.
Global Certification
Red Hat Linux Fees in Bangalore
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Online Classroom PREFERRED
- Live Classes from IIT Faculty & Industry Experts
- Certification from IHUB IIT Roorkee
- Career Services (Mock Interviews, Resume Preparation)
- Placement Assistance upon clearing PRT
- Dedicated Learning Manage
career services
At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalized resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career. Join us and let your journey to a successful future begin with the right support.
At Radical Technologies, we ensure you’re ready to shine in any interview. Our comprehensive Interview Preparation program includes mock interviews, expert feedback, and tailored coaching sessions to build your confidence. Learn how to effectively communicate your skills, handle technical questions, and make a lasting impression on potential employers. With our guidance, you’ll walk into your interviews prepared and poised for success.
At Radical Technologies, we believe that a strong professional profile is key to standing out in the competitive IT industry. Our Profile Building services are designed to highlight your unique skills and experiences, crafting a resume and LinkedIn profile that resonate with employers. From tailored advice on showcasing your strengths to tips on optimizing your online presence, we provide the tools you need to make a lasting impression. Let us help you build a profile that opens doors to your dream career.
Red Hat Linux Course Projects
Infrastructure Provisioning
And Configuration Management
Implementing automated infrastructure provisioning and configuration management using Ansible. This may include setting up servers, networking devices, and other infrastructure components using playbooks and roles.
Applications Deployment
And Orchestration
Automating the deployment and orchestration of applications across development, testing, and production environments. This could involve deploying web servers, databases. middleware, and other application components using Ansible
Continuous Integration
And Continuous Deployment
Integrating Ansible into CI/CD pipelines to automate software. build, test, and deployment processes. This may include automating the creation of build artifacts, running tests, and deploying applications to various environments.