Aug 04, 2021  
PUBLISHED 2021-2022 Credit Catalog 
    
PUBLISHED 2021-2022 Credit Catalog

Data Analytics


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Program Description


Graduates of the Data Analytics post-diploma certificate will possess the knowledge, skills, and aptitude to apply fundamental principles of data analytics. They will learn to align data into the business decision-making process, creating accurate and meaningful storytelling with actionable insights. They will accomplish this using a foundation of data management and ethics.

Program Overview


Fast Facts


  • Online (distance delivery)  OR classroom
  • Applied learning environment
  • Part-time delivery

Bring Your Own Device (BYOD)

The Information Security Analyst program was developed to meet the needs of working professionals who want to specialize in this exciting field.  As the program is being offered via part-time and distance delivery, it is expected that students will provide their own laptop. Classes will be scheduled into e-learning labs with power outlets. Wifi access is available to connect to the network and internet. Laptop specs should meet the following minimum requirements: i5 or i7 processor, 16 GB RAM, 500 GB storage. It may be necessary to subscribe to some specialized software for certain courses.



Your Career


Student Success


This is an intensive program requiring a commitment of both time and energy; students who experience success are those who make their education a priority throughout the program.

We find there is a direct correlation between the time and energy invested to the amount of success achieved. Learners with strong time-management and discipline have a greater propensity to succeed.

Remaining focused and diligent with coursework is important for success in completing the program.

Ideal Candidate

The ideal candidate for the Data Analytics post-diploma certificate has a previous post-secondary diploma or degree. Education in business, economics, finance, etc. would be ideal. You have a strong math background and foundational education in statistics. You have worked with data and are intrigued by the power of data and how it can be analyzed to support good business decision-making. Previous experience working with databases is an asset.

Get started as an undeclared student 

The courses in the Data Analytics program allow for registration into individual courses without going through the SAIT application process. It is important that you read the “Ideal Candidate” statement to be sure that you are a good fit for these courses. You may apply to complete the credential at any time through Apply Alberta at which time you will have to submit transcripts for entrance into the credential. You must apply for prior learning assessment if you wish to get credit for a required course based on previous education or experience.

Credentials and Accreditation


Upon successful completion of this program, graduates will receive a SAIT Data Analytics post-diploma certificate.

Professional Designations and Certifications


Progression


The progression requirement for students taking credit courses is a Term GPA and Total Institutional GPA of 2.0, with the exception of English Language Foundations and Academic Upgrading programs.

Admission Requirements



Applicants must meet one of the following (or equivalent), as well as the English Proficiency requirement*:

  • Post-secondary degree or diploma from a recognized university, institute or college.
  • A combination of education and experience will be considered, upon approval from the Academic Chair. 

* All applicants must demonstrate English language proficiency prior to admission, including students educated in Canada.

Total Credits 24


Program Outcomes


  1. Manipulate data using data science, modeling, ethics, ETL in a business context that is relevant to decision-making.
  2. Contextualize data in a format that maps to business processes, objectives, and aligns data analysis to strategic outcomes.
  3. Build presentations that communicate data analysis effectively and accurately for a business audience using visualizations (dashboards) and storytelling.
  4. Perform statistical and algorithmic analyses on cloud-based and on premise data sets using a variety of tools and techniques.
  5. Explain the use of machine learning and artificial intelligence as it relates to data analysis.
  6. Use industry recognized programs and tools to extract meaning from data.
  7. Demonstrate core strategic, tactical and operational business processes which are driven by data for evidence-based decision making.
  8. Apply fundamental data analytics principles, aligning data and business processes to create accurate, actionable insights.

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