Certified Professional in Data Lake Analytics
-- viewing nowThe Certified Professional in Data Lake Analytics course is a comprehensive program designed to equip learners with essential skills for data lake analytics, a rapidly growing field. This course is critical for professionals seeking to advance their careers in data analytics, machine learning, and AI.
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Course details
• Data Lake Analytics Fundamentals: Introduction to data lakes, big data analytics, and the role of Data Lake Analytics. Understanding of Azure Data Lake and its architecture.
• Azure Data Lake Analytics U-SQL: Deep dive into U-SQL, a query language for big data. Understanding of U-SQL data types, variables, statements, and functions. Hands-on experience with U-SQL scripts and queries.
• Data Lake Analytics Catalog: Exploring the Data Lake Analytics Catalog, including metadata management, data definition, and data partitioning. Understanding of how to create and manage catalog objects.
• Data Lake Analytics Security: Best practices for securing Data Lake Analytics, including access control, data encryption, and auditing. Understanding of Azure Active Directory and Azure policy.
• Data Lake Analytics Performance Optimization: Techniques for optimizing Data Lake Analytics performance, including data partitioning, query optimization, and resource allocation. Understanding of performance metrics and monitoring tools.
• Data Integration with Data Lake Analytics: Integrating Data Lake Analytics with other Azure data services, including Azure Data Factory, Azure Stream Analytics, and Azure Data Bricks. Understanding of data pipelines and ETL processes.
• Data Analytics with Data Lake Analytics: Analyzing data with Data Lake Analytics, including data exploration, data visualization, and machine learning. Understanding of Azure Machine Learning and Azure Synapse Analytics.
• Data Lake Analytics Governance: Best practices for governing Data Lake Analytics, including data quality, data lineage, and data retention. Understanding of Azure Policy and Azure Monitor.
• Data Lake Analytics Best Practices: Advanced topics for Data Lake Analytics, including cost management, disaster recovery, and high availability. Understanding of Azure DevOps and Infrastructure as Code.
Career path
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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