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Data Warehouse Essentials is a course designed to provide a robust understanding of data warehousing concepts, architecture, and best practices. Targeted at aspiring data professionals, this course delivers the knowledge required to design, implement, and optimize data warehouses. Core Learning Objectives: - Understand data warehousing concepts and their importance in modern data management. - Learn architectural components and design considerations. - Explore data modeling techniques, including ER models and star schemas. - Examine ETL processes and data integration from multiple sources. - Get acquainted with popular data warehousing tools and technologies. - Develop querying, reporting, and performance optimization skills. - Ensure security, compliance, and governance in data warehousing. - Understand the relationship between big data and data warehouses. The course starts with an introduction to data warehousing fundamentals, focusing on their importance in data-driven decision-making. It covers data warehouse architecture, components, and design aspects crucial for building efficient systems. Learners delve into data modeling to organize data within a warehouse and cover essential ETL procedures for data integration and cleansing. Practical skills include navigating data warehousing tools and the current technology landscape. Other focus areas include querying, reporting, performance optimization, and maintaining data warehouse security and governance. The course ends with the exploration of big data's interaction with data warehousing, preparing students to address modern data challenges. By the conclusion, participants will enhance their data management skills, becoming adept at designing and managing robust data warehouses in line with business objectives.
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