This course covers the challenges of Big Data technologies, including capturing, storing, analyzing, sharing, and querying data. It also compares traditional structured data with new, large, complex, and unstructured data, and explains how to design a Big Data implementation plan and develop strategies for data-driven solutions using analytics-focused architectural diagrams. In summary, the course explores the five steps of Big Data processing: data sources, acquisition, storage, analysis, reporting, and visualization.
This course will enable you to:
• Plan and implement a Big Data project
• Design a Big Data architecture diagram including structure and technologies
• Gain hands-on experience with popular Big Data storage and computing systems
• Create a relevant architecture diagram for analytics tasks using Azure - Databricks
• Understand Big Data Architectures and Paradigms: Hadoop, MPP, Distributed In-memory
• Learn about Big Data Compute Technologies like Hadoop, MapReduce, Spark, Kafka, etc.
• Bridge the gap between data projects and organizational needs
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