Data Engineering & Management

О курсе

Learn how to design, optimize, and manage modern data systems through this comprehensive course in the Data Engineering & Management Skill Path. You will build critical competencies including designing conceptual, logical, and dimensional data models, applying normalization to relational databases, and evaluating indexes and execution plans to improve query performance. You will also master advanced SQL functions to create derived features, optimize queries for speed, and automate workflows with reusable scripts. Beyond relational data, you will gain practical expertise in integrating external data through APIs, applying programmatic logic and regular expressions to transform unstructured data, and developing multi-step transformation pipelines. You will practice data reconciliation, enforce schemas for consistency, and analyze data lineage to trace and resolve quality issues. Additional focus on OLTP vs. OLAP design, outlier handling, and clustering techniques prepares you to bridge engineering and analytical perspectives. This course brings together expertise from Edureka, Microsoft, Google, Packt, Arizona State University, Maven Analytics, Coursera Instructor Network, and Johns Hopkins University, ensuring a balanced blend of academic rigor and industry relevance. You will progress from relational database foundations to Python scripting, API integration, and Tableau visualizations, preparing you to confidently build scalable, high-quality data systems that deliver business value.

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