Advanced Data Modeling

Develop a working knowledge and familiarity with advanced database concepts such as usage, modeling, automation, storage, optimization and administration. To take this course, you must have completed the previous Database courses. You must also be eager to continue your journey with coding. The Professional Certificates create opportunities so that anyone regardless of education, background or experience can learn high-quality skills to land a high-growth career—no degree or experience required to get started. By the end of this course, you’ll be able to: - Deploy basic data modeling skills and navigate modern storage options for a data warehouse - Apply planning and execution of ETL style database engineering by building upon existing MySQL skills - Develop a working knowledge of the different aspects of managing a database including administration of database operations and concerns, alongside processes and solutions for monitoring, reporting and debugging - Demonstrate data modeling skills within a real-world project environment You’ll gain experience with the following tools and software: - Workbench data modeling software - Syntaxes used to interact with a data warehouse - Extract, transform and loading (ETL) techniques and methods - MySQL data warehouse administration - Data warehouse monitoring and reporting tools - Database debugging and testing tools - Data modeling tools

• Data modeling and management
• Get to grips with fundamental data modeling concepts, with a particular focus on a systematic database modeling process. Then learn to use MySQL Workbench to visually design, model, generate, and manage databases.
• Data warehousing
• Learn about the role of data warehouses in database analytics, the characteristics of a data warehouse and data warehouse architecture. Develop familiarity with the dimensional data modeling approach for data warehousing.
• Advanced data analytics
• Explore the role of advanced data analytics tools and evaluate how they're used to evaluate business performance.
• Model and analyze data
• Apply data modeling to a real world project.