Azure Big Data Analytics Training Course

Did you know that Microsoft recommends a three-step process to building a new big data solution in the Azure cloud: evaluation, architecture, configuration, and production?

Course Overview

The Azure Big Data Analytics Training Course by Alpha Learning Centre is meticulously designed to equip professionals with essential skills in designing, implementing, and managing big data analytics in the Azure cloud environment. This course focuses on everything from data ingestion and storage to advanced analytics and visualisation, ensuring participants can effectively navigate the complex landscape of Azure big data solutions.

Why Select This Training Course?

Selecting this Azure Big Data Analytics Course offers numerous advantages for professionals involved in data engineering and analytics. Participants will gain advanced knowledge of Azure Synapse Analytics, Data Factory, and Databricks. The course provides hands-on experience with industry-standard Azure tools and real-world case studies, enabling attendees to optimise their big data strategies effectively.

For organisations, investing in this training enhances overall analytical capabilities and ensures better data integration. Research shows that organisations implementing comprehensive Azure big data frameworks can achieve better integration between relational and non-relational data sources and enhanced analytical capabilities through platforms like Azure Databricks.

For individuals who complete this course will benefit from enhanced career prospects as they become more valuable assets in their respective fields. Studies indicate that professionals with Azure big data expertise can significantly improve their career trajectory as the field requires understanding of both batch and real-time data processing, while skills in Azure CLI, PowerShell, and Portal administration are in high demand.

Transform your Azure big data capabilities – Register now for this critical advanced training programme!

Who Should Attend?

This Azure Big Data Analytics Training Course is suitable for:

• Data Engineers looking to leverage Azure for complex data solutions
• Data Scientists aiming to scale their machine-learning models
• Business Analysts seeking deep insights from large datasets
• IT Professionals managing Azure data services
• Architects designing Azure data architectures

What are the Training Goals?

This course is designed to enhance your ability to:

• Architect and implement Azure-based big data solutions
• Process and analyse vast datasets with Azure tools
• Optimize data workflows for performance and cost
• Apply advanced analytics features in Azure for business intelligence
• Secure and govern data in Azure environments effectively

How will this Training Course be Presented?

The Azure Big Data Analytics Training Course delivers comprehensive, hands-on training through proven methodologies designed to maximise learning outcomes and practical skill development. Our expert instructors employ the following methods:

• Hands-on labs using Azure’s latest offerings
• Interactive workshops with real-time data scenarios
• Expert-led sessions on Azure data services
• Case studies from industry leaders using Azure for big data
• Peer collaboration on project-based learning tasks

Each delivery method is carefully integrated to ensure participants gain both theoretical knowledge and practical experience. The course structure promotes active engagement and real-world application, allowing participants to develop crucial analytical and strategic skills within a supportive learning environment.

Join us to experience this dynamic and effective learning approach – Register now to secure your place!

Course Syllabus

Module 1: Mastering Azure Synapse Analytics 

• Leveraging Azure Synapse for integrated analytics
• Configuring and managing SQL pools for performance
• Implementing Apache Spark pools for big data processing
• Optimizing data warehousing with Synapse pipelines
• Real-time analytics using Synapse Link for Azure Cosmos DB
• Data integration strategies with Synapse Studio
• Security and compliance in Azure Synapse environments
• Advanced querying techniques for analytical insights

Module 2: Data Ingestion with Azure Data Factory 

• Designing robust data ingestion pipelines
• Utilizing data flows for complex transformations
• Implementing mapping data flows for scalability
• Managing data movement across on-premises and cloud
• Monitoring and troubleshooting ADF operations
• Scheduling and orchestration of data workflows
• Integration with Azure Databricks for ETL processes
• Handling data from IoT devices and streaming sources
• Security practices in Azure Data Factory
• Cost optimisation strategies for data ingestion

Module 3: Azure Databricks for Data Engineering 

• Advanced Spark job execution in Azure Databricks
• Delta Lake for ACID transactions on big data
• AutoML features within Databricks for model tuning
• Collaborative notebooks for team-based data science
• Performance tuning of Spark applications
• Integration with MLflow for model lifecycle management
• Securing Databricks environments in Azure
• Best practices for Databricks cluster management

Module 4: Real-Time Analytics with Azure Stream Analytics 

• Architecting real-time data processing solutions
• Handling event streams with windowing functions
• Complex event processing for anomaly detection
• Integration with Power BI for real-time dashboards
• Scaling Stream Analytics jobs for high throughput
• Monitoring and scaling in response to data ingestion rates
• Outputting to multiple sinks for varied use cases
• Managing data retention and compliance in streaming
• Optimizing costs and performance in Stream Analytics

Module 5: Azure HDInsight for Big Data Processing 

• Deploying and managing Hadoop clusters in Azure
• Using Apache Spark on HDInsight for distributed computing
• Interactive querying with Hive LLAP on HDInsight
• Kafka on HDInsight for real-time data ingestion
• Performance tuning of Hadoop workloads
• Security and governance of HDInsight clusters

Module 6: Data Lake Storage Gen2 for Comprehensive Data Storage 

• Structuring data lakes for analytics readiness
• Implementing a hierarchical namespace for better access control
• Managing data lifecycle with Azure Storage Lifecycle Management
• Integration with Azure Synapse for data lake analytics
• Encryption and security best practices for Data Lake Storage
• Optimizing storage for cost and performance
• Handling streaming data directly into Data Lake
• Accessing data with ABFS driver for Azure Databricks
• Advanced querying patterns with Azure Data Explorer
• Ensuring data lineage and metadata management

Module 7: Advanced Analytics with Azure Machine Learning 

• Deploying and managing ML models at scale
• Utilizing Azure ML for automated machine learning
• MLOps for model versioning and lifecycle management
• Integration with Azure Databricks for ML workflows
• Performance tuning of ML models in production
• Ethical AI practices and model fairness
• Security considerations for ML models in Azure
• Real-time scoring with Azure ML endpoints
• Cost management in Azure Machine Learning

Module 8: Azure Cosmos DB for NoSQL Data Solutions 

• Multi-model database capabilities in Cosmos DB
• Implementing global distribution for data residency
• Tuning consistency levels for performance and availability
• Integration with Azure Functions for serverless analytics
• Querying and indexing for high-performance operations
• Managing data consistency in distributed systems
• Security features and data encryption at rest and in transit

Module 9: Data Visualisation and BI with Power BI on Azure 

• Advanced data modelling techniques in Power BI
• Leveraging Azure Analysis Services for large datasets
• Real-time analytics with Power BI streaming datasets
• Embedding Power BI into applications for custom analytics
• Performance considerations for large BI workloads
• Utilizing composite models for complex data scenarios
• Security and governance in Power BI environments
• Automating report generation with Power BI APIs
• Integration with other Azure services for comprehensive insights

Module 10: Azure Data Governance 

• Implementing Azure Purview for data cataloguing
• Data lineage tracking across Azure services
• Managing data classification and protection
• Compliance with privacy regulations using Azure
• Data quality frameworks using Azure tools
• Automating data governance policies
• Monitoring and enforcing data policies

Module 11: Optimising Azure Costs for Big Data 

• Assessing and managing Azure cost for data services
• Right-sizing Azure resources for data workloads
• Implementing auto-scaling for dynamic data demands
• Cost implications of different Azure storage classes
• Optimizing queries and data operations for cost efficiency
• Understanding Azure billing models for data analytics
• Strategies for reserved instances in data environments

Training Impact

The impact of Azure big data analytics training is evident through various real-world case studies and data, which demonstrate the effectiveness of structured programmes in enhancing data processing capabilities and analytical insights.

Research indicates that organisations implementing comprehensive Azure big data solutions can achieve significant improvements in data integration and analytical capabilities. According to industry analysis, big data solutions require a variety of different tools ranging from data sources and integration to data models and visualisation, and Azure provides a comprehensive offering covering all requirements needed to build and manage a big data solution.

These case studies highlight the tangible benefits of implementing advanced Azure big data techniques:

• Improved data integration between diverse sources
• Enhanced analytical capabilities through Azure platforms
• Increased efficiency in real-time data processing
• Strengthened data governance and security

By investing in this advanced training, organisations can expect to see:

• Significant improvement in data processing capabilities
• Improved ability to handle complex big data scenarios
• Enhanced decision-making capabilities through advanced analytics
• Increased competitiveness through comprehensive Azure big data strategies

Transform your career and organisational performance – Enrol now to master Azure Big Data Analytics!