Prerequisites: INFS 492
This course focuses on practical methods for in-database data preparation and manipulation to extract analytical insights out of a large or big data repository. The concept of big data, distributed computing frameworks, and massively parallel processing databases are also covered.
Students will become proficient using open source databases, performing extensive advanced SQL programming, writing scripts and manipulating strings, numbers, data, etc. within a database.
Outcomes: Implement Advanced Data Queries: Conduct advanced searches, hierarchical queries, and implement range-based filtering to address complex data analysis requirements; Master Advanced SQL Techniques: Develop expertise in advanced SQL programming, including \\nstring manipulation, numerical calculations, date handling, and metadata queries; Analyze and Prepare Data for AI: Utilize in-database data preparation techniques to transform raw data into actionable insights, a critical step for AI model development and implementation.
This course focuses on practical methods for in-database data preparation and manipulation to extract analytical insights out of a large or big data repository. The concept of big data, distributed computing frameworks, and massively parallel processing databases are also covered.
Students will become proficient using open source databases, performing extensive advanced SQL programming, writing scripts and manipulating strings, numbers, data, etc. within a database.
Outcomes: Implement Advanced Data Queries: Conduct advanced searches, hierarchical queries, and implement range-based filtering to address complex data analysis requirements; Master Advanced SQL Techniques: Develop expertise in advanced SQL programming, including \\nstring manipulation, numerical calculations, date handling, and metadata queries; Analyze and Prepare Data for AI: Utilize in-database data preparation techniques to transform raw data into actionable insights, a critical step for AI model development and implementation.