5 courses with the subject DBA, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DBA 110Database Concepts3.0
This course introduces database design and creation using a DBMS product. Emphasis is placed on data dictionaries, normalization, data integrity, data modeling, and creation of simple tables, queries, reports, and forms. Upon completion, students should be able to design and implement normalized database structures by creating simple database tables, queries, reports, and forms.
This course introduces the role of a Google data analyst and how to make data-driven decisions using effective questions, data transformation and analyzation processes. Emphasis is placed on setting up a data toolbox, spreadsheets, database and query basics, visualization basics, effective communication techniques, and data validation. Upon completion, students should be able to review assessments, use formulas and calculations to analyze datasets, create queries, use visualization tools and communicate effectively with stakeholders.
This course is designed to develop SQL programming proficiency. Emphasis is placed on data definition, data manipulation, and data control statements as well as on report generation. Upon completion, students should be able to write programs which create, update, and produce reports.
This course introduces the role of an advanced Google data analyst and how to make data-driven decisions using effective questions, data transformation, analyzation processes, visualization and programming. Emphasis is placed on setting up a design thinking, data-driven storytelling, dashboards, R programming, job portfolios and technical expertise. Upon completion, students should be able to create a data-driven storyboard, develop dashboards and presentations, create analytical reports using R, and showcase technical analytical skills.
This course introduces data warehousing and data mining techniques. Emphasis is placed on data warehouse design, data transference, data cleansing, retrieval algorithms, and mining techniques. Upon completion, students should be able to create, populate, and mine a data warehouse.
