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Course Description
This course is 42 learning hours inclusive of 4 hours of live sessions. It is recommended that students spend an average of 7 hours per week on this course.
The final course in the Certificate in Data Management for Professionals looks at Codd’s relational database theories. NoSQL and NewSQL will both be explored and compared, along with traditional data warehouses and data lakes. The course concludes with a lesson on big data.
Course Outline
- Week 1: The Ubiquity of Relational Databases and Codd’s Relational Database Theories
- Week 2: NoSQL, NewSQL - The Argument Against the Traditional Relational Database
- Week 3: Traditional Data Warehouses vs Data Lakes
- Week 4: Big Data - Organizational Readiness
What You Will Learn
- An overview of Codd’s relational database theories
- A comparison of NoSQL and NewSQL
- The differences between traditional data warehouses and data lakes
- The importance of big data
Notes
By enrolling in this course, you will be automatically enrolled in the Certificate in Data Management for Professionals.The Faculty of OLCD recommends an intermediate level of English language proficiency for the most effective learning and participation in our online and face-to-face courses. A list of the minimum recommended scores on some common English tests can be found on our website. If you have questions about your English language proficiency and ability to succeed in this course, please contact openlearning@dal.ca.
Prerequisites
Recommended For
- Professionals from accounting, sales and engineering who are involved in evaluating, implementing and/or using information management systems
- Industry workers from healthcare, manufacturing and finance who assess, apply and/or employ information management systems
- Those with one to two years of experience working with any enterprise information system (such as an ERP or data warehouse)
Applies Towards the Following Certificates
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Eleanor Smith is a seasoned IT Professional, has taught a variety of technology subjects (Oracle cloud systems, data management, and programming) for both academic institutions and corporate clients. She was one of the first instructors in McMaster’s Big Data Analytics continuing education program launched in 2017 and helped develop its curriculum to promote data literacy in the context of Big Data.