Data Management and Analytics Post-Diploma Certificate (2022)

Data Management and Analytics Post-Diploma Certificate (1)

Post-Diploma Certificate

The Data Management and Analytics Post-Diploma Certificate prepares learners to uncover insights from unstructured data sets to inform data-driven decision making.

Women in Technology Bursary APPLY NOW

Technology/ Data Management and Analytics Post-Diploma Certificate

Location
Start Dates
  • September 05, 2023
Duration

2Terms

Program Delivery
  • In Class

    A course delivery mode where learning activity is scheduled and takes place in a classroom or similar setting at a college facility. May include lecture, laboratory, and seminar components.

i

  • In Class - A course delivery mode where learning activity is scheduled and takes place in a classroom or similar setting at a college facility. May include lecture, laboratory, and seminar components.
Tuition & Fees

Domestic: $12,274
International: $34,462

Program Description

The Data Management and Analytics Post-diploma Certificate prepares learners to uncover insights from unstructured data sets to inform data-driven decision making. Learners will determine data requirements, plan for the data life cycle, model data, and use information technology tools to gather data and interpret results. Graduates of the program will have experience with relational database systems, data warehousing, data quality improvement, and visual analytics, along with an introduction to working with big data. Graduates will be able to design data analytics projects to help organizations across sectors make informed and actionable decisions. Resolving real-life business and organizational challenges will be central to project work.

Potential Graduate Career Opportunities

Exciting career opportunities await in the public and private sectors, including companies and corporations, non-profit agencies, and government agencies.

  • Data Analyst
  • Database Administrator
  • Data Merger Specialist
  • Data Analytics Professional
  • Data Architect

Course Listings

Request more information How to apply

Domestic Applicants

WelcomeCentre
South Campus – Main Floor
info@bowvalleycollege.ca
403-410-1402

International Learner Applicants

International Education
North Campus – Third Floor
international@bowvalleycollege.ca
403-410-3476

Admission Requirements

  • Completion of a diploma or equivalent in business administration, information technology, engineering, or software development
  • Credit in Math 30-1 or Math 30-2 or equivalent

English language proficiency requirements

For applicants whose first language is not English, please review English language proficiency requirements.

Please note

  • Learners are expected to have programming experience
  • A laptop computer meeting minimum specifications is required for this program (see below)
  • Additional course-specific software may be required

Laptop Specifications

A laptop computer with course applicable software will be required (specifications below)

  • Intel quad core CPU (i7) or later generation
  • 16GB RAM or greater
  • 512 GB SSD or greater (Hard Drive & storage)
  • On-board integrated (Video card)
  • 15 inches or greater screen
  • Windows 10 Pro/education 64-bit (MacOS is not supported)
  • Portable hard drive (for data backup)

Domestic Applicants

WelcomeCentre
South Campus – Main Floor
info@bowvalleycollege.ca
403-410-1402

International Learner Applicants

International Education
North Campus – Third Floor
international@bowvalleycollege.ca
403-410-3476


Data Management and Analytics Post-Diploma Certificate (2)
Employment Rate

100%

Data Management and Analytics Post-Diploma Certificate (3)
Training Related Employment Rate

75%

Based on 2019-2020 domestic and international students who self-reported finding employment or training-related employment within 6-12 months after graduating.


Women Pivoting in Tech Entrance Bursary

Funded by the Alberta Women’s Economic Recovery STEM grant, this bursary supports women pursuing careers in the STEM field of technology, aiming to reduce financial barriers.

Award amounts:

  • $5,000 in your first semester
  • $5,000 in each of your following semesters

Apply today and be eligible for the Women Pivoting in Tech Entrance Bursary.

Apply for Bursary

Term 1

Required CoursesCredit

DATA3402 - Data Programming Credits3

Understanding the data-driven programming methodology and having a sound programming background are foundational skills for anyone interested in working with data. This course introduces students to the principles of programming and application design. In addition, students begin to apply the concepts of data structures and algorithms to develop data-driven software applications.

DATA3403 - Designing Data Analysis Projects Credits3

Effective data analysis requires the integration of business understanding and data understanding. In this course, learners synthesize information about common business processes, workflows, and management strategies across a range of sectors (such as sales, marketing, accounting, quality improvement, product/service delivery, product development, and human resources), and their associated data needs. Learners then apply this knowledge to real-world business contexts to identify and define business goals and design appropriate data projects

DATA3404 - Data Acquisition Credits3

The quality of a data analysis project is limited by the quality of the data used. In this course, learners locate and select relevant, high-quality data that meets the requirements and constraints of a project. Learners then extract data from different sources (a database, a website) using the appropriate techniques(SQL, web-scraping, and Application Programming Interface (API)).

Additional Performance Standards:
This course, along with Data Wrangling, make up the Data Acquisition and Wrangling competency; competency assessments in both courses must be successfully completed to be deemed competent.

In order to be successful in this course, learners must be competent in the Data Programming course outcomes.

DATA3405 - Data Wrangling Credits3

Data wrangling is an incredibly important step in a data analysis project. Once data has been collected, it must be prepared - reviewed, cleaned, structured, and enriched - prior to analysis. In this course learners profile a dataset, reshape the data structure, identify and clean data issues (such as missing data, duplicates, outliers, coding issues), and enrich data through augmentation, aggregation, or calculation. The result of data wrangling is a finalized dataset that is well documented and ready for analysis.

Additional Performance Standards:
This course, along with Data Acquisition, make up the Data Acquisition and Wrangling competency; competency assessments in both courses must be successfully completed to be deemed competent.
In order to be successful in this course, learners must be competent in the Math for Data Analytics and Data Programming course outcomes.

DATA3408 - Data Visualization I Credits3

A key role of an analyst is to present insights in a meaningful and compelling way so that stakeholders can fulfill business objectives. In this course, learners apply the principles of visual storytelling to design visualization elements, reports, and interfaces (e.g. dashboards) that meet stakeholder needs and support decision making.

Additional Performance Standards:
This course, along with Building and Presenting Data Visualizations, make up the Visualizing Data and Insights competency; competency assessments in both courses must be successfully completed to be deemed competent.
In order to be successful in this course, learners must be competent in the Math for Data Analytics and Data Programming course outcomes.

MATH3902 - Mathematics for Data Analytics Credits3

This course is specifically focused towards supporting the mathematical principles required to apply the concepts of data analysis and big data analytics. Learners apply concepts such as probability, distributions, regression, topological analysis, and descriptive and inferential statistics to data-related contexts.

Term 2

Required CoursesCredit

DATA3406 - Data Analysis I Credits6

The first step in exploratory data analysis (EDA) is pattern identification. In order to identify patterns within the data, learners utilize descriptive statistical methodology that is relevant and meaningful to the project goals. Learners use graphical analysis to explore relationships and correlations within the dataset. A variety of methods are used to handle missing data and outliers within the dataset. To categorize the data, learners build unsupervised learning models. Learners summarize the outcomes of their analysis from unsupervised learning models and use the outcomes to develop actionable business insights and recommend further analysis.

Additional Performance Standards:
This course, along with Data Analysis II, make up the Performing Data Analysis competency; competency assessments in both courses must be successfully completed to be deemed competent.
In order to be successful in this course, learners must be competent in the Math for Data Analytics and Data Programming course outcomes.

DATA3407 - Data Analysis II Credits3

Using identified relationships within the data learners build simple predictive models based on regression and classification. Learners fit the data to the model, assess the model's performance and make adjustments the model's parameters. Learners summarize the outcome(s) of their analysis from predictive models and use the outcome(s) to develop actionable business insights. Learners assess further modelling opportunities and make recommendations for further data analysis.

Additional Performance Standards:
This course, along with Data Analysis, make up the Performing Data Analysis competency; competency assessments in both courses must be successfully completed to be deemed competent.

DATA3409 - Data Visualization II Credits3

In this course, learners apply a range of techniques to realize any design vision. Learners integrate their technical and communication skills to build and refine simple and complex visualizations to optimize effectiveness. Finally, learners close off a project, ensuring that decision makers have what they need to make decisions.

Additional Performance Standards:
This course, along with Designing Effective Visualizations, make up the Visualizing Data and Insights competency; competency assessments in both courses must be successfully completed to be deemed competent.

DATA3999 - Data Management and Analytics Capstone Project Credits6

Working alone or in a small team, students research, design, develop, and implement an applied big data analytics research project to satisfy a real organizational or community need. Students are expected to apply all of their knowledge and skills to produce a functioning prototype of their project idea.

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