CIND 110 - Data Organization for Data Analysts
Course Description
This course provides a foundation in data management for data analysts. Topics include database architectures, formation of queries, queries themselves, data warehousing, relational database systems, NoSQL, and responsibilities of data management professionals.What Will You Learn?
This course provides database skills in the application of knowledge transfer, advanced critical thinking, research application, and report writing with respect to big data and data analytics.
Learn how to:
- Use a practical procedural language to define, construct, manipulate, share, and protect a structured database.
- Reverse and Forward engineer a database to create valid logical models and migratable snapshots.
- Manipulate the basic components of a relational model, its entity/referential integrity constraints, and update operations.
- Extract data from data and document-centric databases (for example, XMLs and JSONs) using XPATH and XQuery expressions.
- Differentiate between database and information retrieval systems.
- Index, search and retrieve information from large collection of unstructured documents using statistical approaches.
- Use data mining techniques, such as association rules, sequential patterns, and classification trees for big data analyses.
Notes
The deadline to enroll in CIND 110 for Spring term (courses that begin the week of May 3, 2021) is April 29, 2021.
The deadline to enroll in CIND110 for Summer term (courses that begin the week of June 21, 2021) is June 16, 2021.
Students will also not be allowed to swap between sections of the Data Analytics courses after April 29, 2021 for Spring term and June 16, 2021 for Summer term.
Course materials, video lectures and discussions are delivered and facilitated online within the D2L Learning Management System.
Throughout the semester, student questions related to course content may be answered either by the instructor on discussion board or by an online tutor via email.
Relevant Programs
- Data Analytics, Big Data, and Predictive Analytics : Required Courses