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Course Outline
Foundations of Azure Synapse Analytics
- System overview and strategic positioning
- Core functional capabilities and technical scope
- Evaluation against alternative analytics frameworks
Implementation of Azure Synapse Analytics
- Provisioning of the Synapse workspace
- Configuration of data lake storage components
- Administration of user identities and access governance
Data Integration and Management
- Methodologies for data ingestion
- Execution of ETL workflows via Azure Data Factory
- Strategies for data storage and structural organization
Development of Big Data Solutions
- Introduction to Spark pools within Azure Synapse
- Processing of large-scale datasets using Spark
- Integration protocols with Azure Machine Learning
Data Querying via Serverless SQL Pools
- Overview of serverless SQL pool architecture
- Cross-source data querying mechanisms
- Performance tuning and optimization strategies
Security and Compliance
- Data protection protocols and encryption standards
- Access controls and privacy regulations
- Monitoring systems and audit trails
Data Visualization and Analysis
- Integration with Power BI and external visualization platforms
- Construction of analytical dashboards and reports
- Dissemination of insights across organizational boundaries
Resource Management and Operational Best Practices
- Architectural guidelines for public sector operations
- Management and scaling of computational resources
Conclusion and Recommended Next Steps
Requirements
- Fundamental understanding of cloud computing principles
- Proficiency in data warehousing principles and practices
Target Audience
- Data engineers
- Data scientists
- Cloud infrastructure professionals
14 Hours
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Equipped with examples