Applied Data Analytics

​This intensive, hands-on course is the prerequisite for follow-on database courses in several BCIT Computing programs. Students are introduced to relational database design concepts and industry standards. COMP 1630 starts with tools and processes for data modeling in Relational Database Management Systems (RDBMS). Labs and exercises take place in a Windows 11 PC environment. There is also a heavy focus on the Structured Query Language (SQL) to define and manipulate data. Topics include functional dependencies, normalization, database design methodologies, entity relationship modeling and the use of UML as a diagramming notation. Advanced topics include: an introduction to SQL, DDL- data definition language and DML- data manipulation language, views, security, transaction management, triggers and stored procedures. Current trends in database such as Replication, Data Warehousing, Online Analytical Processing (OLAP), using databases on the web and in the cloud are discussed. Students in are required to participate in group work, there is significant reading and assignments required outside of class. Online activities via the BCIT Learning Hub are mandatory. COMP 1630 is a required course for the Applied Database Administration and Design (ADAD) Associate Certificate; the Applied Data Analytics Certificate (ADAC) and the Computer Systems Certificate (CSC). It is also equivalent to the Full-time COMP 2714 and ACIT 1630 database courses. Upon successful completion, participants will be able to design and implement a database application and be prepared to move on to higher level database courses including: COMP 3677 Introduction to MS Server Administration Part 1, COMP 3678 SQL Server Development; COMP 3679 Business Intelligence (BI) Tools, and COMP 3839 Data Quality Improvement.
Prerequisite(s):

• 60% in COMP 1002

​​Microsoft Excel is a powerful tool that can be used to analyse, communicate and manage information. Those with no prior spreadsheet experience will acquire expert level applied skills in the latest version of MS Excel. This instructor lead, hands-on course focuses on best practices used to create meaningful workbooks and how to master the techniques and time saving shortcuts for the daily use of MS Excel. Students learn to use MS Excel Ribbon interface with contextual tabs, Quick Access Toolbar and how to make use of templates, styles, pivot tables, what if analysis tools and macros via lectures, lab exercises and assignments outside of class. Topics include: creating, editing, formatting and saving a worksheet, sorting, filtering, slicers, applying formulae, functions, importing and exporting data, and consolidating data in multiple worksheets. This course is required in the Applied Data Analytics Certificate (ADAC) and the Applied Computer Applications (ACA) Associate Certificate from BCIT Computing Part-time Studies. By the end of this course, successful participants will be expert end users of MS Excel.
Prerequisite(s):

• COMP 1002

This hands-on course introduces descriptive statistics, basic inferential statistics, linear regression, and probability concepts and calculations. Emphasis throughout the course will be placed on using statistical methods for the exploration and analysis of data sets. This introduction will enable students to use statistics for data analysis, will prepare them for “Data Analytics/Mining,” and covers topics appropriate for anyone seeking a first statistics course. Labs and exercises employ standard graphical methods to represent statistical data. Hypothesis tests, including ANOVA, are used to test for significant differences between multiple groups. Students will be introduced to the open source R Programming language, a statistical analysis tool used to extract meaningful information from a variety of scientific, industrial and commercial data sets. Upon successful completion, students will be able to carry out calculations, perform statistical decision making and solve problems with involving collected data. This course prepares the student to move on to MATH 3060 and is a required course for the Applied Data Analytics Certificate offered by BCIT Computing.
Prerequisite(s):

• Math 12 Pre-Calculus or equivalent.

​​​Business Analysis and Systems Design is the study of concepts, processes and tools that professionals use to plan and develop information systems to industry standards. Computer Systems Certificate (CSC) students must complete COMM 1103 or COMM 1106 prior to COMP 2831. This course assumes that all participants have strong English communication and interpersonal skills. Students must provide their own current model PC, i5 or higher equivalent processor, 8 GB of RAM minimum, and 256 GB minimum storage. High-speed internet access is needed for online sections and for homework. Beginning with an introduction to the Software Development Life Cycle (SDLC), students work in teams to initiate the system process, analyze problems, discover requirements and create a logical design. Participants will work in groups to ask implicit questions in order to make better decisions. They will then document detailed communication plans prior to developing an information system. COMP 2831 provides the foundation for all is a required in 6 BCIT Computing development credentials. Topics include: techniques used in the discovery of business requirements, traditional approaches to data and process modelling. There is an overview of Object-Oriented Modelling techniques using the Unified Modelling Language (UML) as well as an introduction to Project Management. Please Note: Attendance, participation in class and the BCIT Learning Hub are mandatory. Students may have an average total time commitment of 13+ hours per week; 3 hours of synchronous class time, a 1-hour online component, plus 9+ hours of homework each week. Participants must be able to work in groups, to provide detailed written materials and to make presentations of their designs. Upon completion, successful students will be able to use industry standard tools and methods to analyze, design, document, present, implement information systems and move on to COMP 2833 Agile Methods and the Scrum Framework. ​
Prerequisite(s):

• 60% in COMP 2501 or 60% in COMP 1630

​This hands-on course has replaced COMP 2454 as of September 2024. Following on from COMP 1630, students who understand data modelling and Structured Query Language (SQL) programming are introduced to Python as a tool for data analytics. ​Starting with an installation and overview of the Python IDE; students will explore Python programming and are introduced foundational programming concepts: Variables, Conditions, Operators, Loops, Functions, Arrays, Dictionaries and DataFrames. Exercises and labs explore data analysis using simple statistics with Python. There is an introduction to string manipulation, Regression, Aggregation, and object-oriented structures with Python used in data analysis. Participants are shown how to use Python for basic graphing. COMP 2853 is a required course in the Applied Data Analytics Certificate (ADAC) from BCIT Computing. Upon completion successful students will be able to use Python to perform exploratory data analysis and as preparation for data modeling/data cleaning in the follow-on ADAC courses.
Prerequisite(s):

• 60% in COMP 1630

​This hands-on course follows on from COMP 1630, COMP 2362 (or COMP 2364) and MATH 1060. It introduces data analytics fundamentals to students who have previously acquired skills in Excel spreadsheets, database systems, Structured Query Language (SQL) programming and statistics. Starting with an overview of the business cycle for data mining, students learn how to translate a business problem into a data mining problem. Through a number of problems and case studies, students will build, assess, and deploy different models to gain insights into the data by testing probable hypotheses using primarily SQL and Excel. Discussions include the fundamentals of using the R Language for data analytics. Labs and exercises include: using advanced analytics with SQL, advanced Excel and R Studio to clean data and perform analysis. Participants will gain experience with data exploration, testing hypothesis, and predictive analytics. This is a required course in the Applied Data Analytics Certificate, ADAC from BCIT Computing. Upon successful completion, participants will be able to identify the process of data analysis, the roles of data analytics practitioners and how to create analytics models. Students will be prepared to move on to MATH 3060 Advanced Statistical Techniques for Data Analytics and COMP 4254 Advanced Topics in Data Analytics.
Prerequisite(s):

• 60% in COMP 1630 and (60% in COMP 2362 or 60% in COMP 2364) and 60% in MATH 1060

​Continuing on from COMP 1630 , this course is aimed at students who already understand relational database, data modeling, using spreadsheets and the importance of improving Data Quality (DQ). Topics include the business impact of Data Quality, data profiling techniques, capability, and maturity models. Data Governance, DQ improvement roadmaps and approaches to gaining executive support for DQ improvement are discussed. In class labs, homework assignments and a project focus on how to use Data Quality techniques and tools. COMP 3839 is a required course in the Applied Database Administration and Design (ADAD) Associate Certificate; the Applied Data Analytics Certificate (ADAC) and an elective in the Computer Systems Technology (CST FLEX) Diploma. ​Successful participants learn how to apply a data quality framework to data migration projects and are better prepared to move on to higher-level Database, Business Intelligence and Data Analytics courses.
Prerequisite(s):

• 60% in COMP 1630

This hand-on course offers and in-depth overview of key topics in information technology (IT) security and how to apply best practices for securing computer systems. COMP 3704 starts with an introduction to IT security principles prior to discussion risk terminology, IT security controls, policies, and standards. Topics include security awareness, risk mitigation and control administration. Data and application security, cryptography, information handling best practices, privacy and regulatory issues are also discussed. Labs and exercises include vulnerability assessment, penetration testing, incident response, disaster recovery, and forensic analysis to gain practical experience. COMP 3704 is a required course in BCIT's Applied Data Analytics Certificate (ADAC) and the Computer Systems Technology (CST) FLEX Diploma. Upon completion of this course, successful participants will be able to identify common cyber threats and use standard controls to protect information assets.
Prerequisite(s):

• 60% in COMP 1002

Continuing on from COMP 1630, this hands-on course is a primer for data warehouse and data analytics with Big Data. Students must already understand industry standards in data modelling, relational database design and creating reports with SQL. COMP 3841 begins with an exploration of different Big Data systems. Participants must provide their own current model Windows capable PC, i5 or higher equivalent processor, 8 GB of RAM minimum, and 256 GB minimum storage. High-speed internet access is needed for online sections and for homework. Labs and assignments use a web browser to access course content. Exercises focus on data ingestion, data extraction, data transformation, accessing/querying data, and data visualization. Students conduct a big data analysis with practical, real-world examples and focus on how to populate and analyze vast data sets using a case-study approach. Topics include an overview of different data stores, querying data with visualizations, and an overview of Extract, Transform and Load (ETL) process in the data warehouse. COMP 3841 is a required course in the Applied Data Analytics Certificate (ADAC) and an elective in the Computer Systems Technology (CST FLEX) Diploma. Upon completion, successful students will be able to leverage and maintain a large-scale data warehouse for Business Intelligence.​
Prerequisite(s):

• 60% in COMP 1630

​This hands-on course follows on from MATH 1060 - Statistics for Data Analysis and introduces the students to many of the techniques used in the field of data analytics. This introduction will enable students to use general classification and predictive analysis methods. Methods appropriate for scientific data are also discussed. Labs and projects using the open source statistical analysis tool, R, build on the skills learned in Math 1060 to apply these advanced techniques. Upon successful completion, students will be able to effectively analyze large and small data sets while adhering to sound statistical principles. This course is required for COMP 4254 in the Applied Data Analytics Certificate offered by BCIT Computing.
Prerequisite(s):

• 60% in MATH 1060

​Power BI is a Microsoft collection of tools and an analytics service for data visualization and business intelligence reporting. BCIT Computing offers a series of MS Power Bi courses. COMP 2156 is a hands-on intro course designed for database professionals, data analysts, business analysts and managers. It follows on from COMP 2362 or COMP 2364, it assumes that students have an understanding of statistics for data analysis and advanced functions of MS Excel. Students begin with a brief introduction to the building blocks of Microsoft Power BI and its related services. They are shown how to get a variety of data into the Power BI Desktop from multiple sources. In class labs and exercises focus on how to model, explore, clean and transform simple data for business reports. Topics include: Data Analysis Expressions, DAX, relationships and Data Visualization. Labs and assignments are designed to provide best practices that can be transferred to the workplace. Participants must provide their own current model PC capable of running Windows 10 and MS Excel, with an i5 or higher equivalent processor, 8 GB minimum RAM, and 256 GB minimum storage. High-speed internet access is needed for online sections and for homework. COMP 2156 is an elective in several BCIT Computing credentials including the CST Diploma (FLEX), and a required course in the Applied Data Analytics Certificate (ADAC). By the end of this course successful students will be able use the Power BI unified analytics platform to build and publish high quality dashboards to the web. They will be prepared to move on to the next level COMP 3156 –MS Power BI Optimization and COMP 3157–MS Power BI Advanced Data Visualization.
Prerequisite(s):

• 60% in COMP 2362 or 60% in COMP 2364

​This hands-on course is designed for database professionals, data analysts, business analysts and managers, who want to analyze and visualize data from a variety of sources. Students begin with a foundation in data visualization techniques and principles. Effective data analysis techniques, and industry standard best practices are discussed. Through hands-on labs, assignments, projects and group work, participants learn how to build insightful and interactive dashboards. Participants learn to present compelling visuals via lab exercises and assignments. Tableau dashboard performance considerations are discussed. Students registered in COMP 2256 will receive a student license for Tableau software for their home machines for the duration of the course and have access to a Tableau subject matter expert with industry experience. This course is an elective in five School of Computing and Academic Studies credential programs; Computer Systems Technology Diploma (CST/PTS), Applied Computer Information Systems (ACIS), Applied Computer Applications (ACA), Applied Database Administration and Design (ADAD) and Technical Writing. COMP 2256 is a requirement for the Applied Data Analytics Certificate (ADAC). A project presentation is required and designed to help the students become better communicators. By the end of this course successful participants will be able to produce highly interactive graphs, reports and dashboards that access and visualize data from a multiple sources. We recommend that students working toward a Computing credential complete COMP 1630 first.
Prerequisite(s):

• COMP 1002

​​Following on from COMP 2156 , and parallel to COMP 3157, this hands-on advanced course was designed for Business Intelligence and Data Analysts. Students who already know how to use Power BI to build and publish reports begin with an in-depth introduction to Star Schema and its relevance to optimal Power BI data modeling. COMP 3156 in-class labs and exercises focus on specific strategies to optimize large complex Power BI data models and how to leverage Power BI Service in the cloud for fast performing reports. Topics include relational data modeling in Power BI, Designing Import, DirectQuery, and Composite Data Models. There is also an in-depth explanation of Power BI Service Performance Monitoring. Tabular Editor and DAX Studio are also discussed. Labs and assignments include managing security permissions, data visibility based on role as and leveraging specialized third-party tools. Tabular Editor and DAX Studio are used to monitor and evaluate data model performance. Participants must provide their own current model PC capable of running Windows 11 and MS Excel, with an i5 or higher equivalent processor, 8 GB minimum RAM, and 256 GB minimum storage. High-speed internet access is needed for online sections and for homework. COMP 3156 is an elective in several BCIT Computing credentials including the CST Diploma (FLEX), and the Applied Data Analytics Certificate (ADAC). By the end of this course, successful students will be able to build advanced, optimized data models and use the Power BI Service cloud environment.​ This course will be offered in the Winter (January) and Spring (April) terms.
Prerequisite(s):

• 60% in COMP 2156

This practical course is for BCIT Computing and Business students who want to learn about laws and policies applicable to the Internet and information technology, as well as intellectual property rights. Topics covered in this course include the following: copyright, patents, trade secret, trademarks, domain names, cybercrime, privacy, e-commerce and online contracts, and online advertising.
Prerequisite(s):

• No prerequisites are required for this course.

This is the final course and project for the Applied Data Analytics Certificate (ADAC) from BCIT Computing. Students must have completed all specific prerequisites in order to register. COMP 4254 is built on top of: Python Fundamentals for Data Analysis, Data Analytics Fundamentals, and Advanced Statistical Techniques for Data Analytics. Students must have experience using data visualization tools, be able to use R and apply statistical methods with algorithms in order to develop their final project. COMP 4254 is a BYOD (bring your own device) course, participants must provide their own current model PC with an i5 or higher equivalent processor, 8 GB of RAM minimum, 256 GB minimum storage and high-speed internet access. Participation is mandatory. Attendance is required during scheduled class hours and students should expect an additional 10+ hours for reading and homework each week. Building on statistics for data mining, students will make use of previous tools and technologies used through out the program. A combination of R, or Python, and Data Analysis tools and visualization techniques will be integrated into an advanced data analytics project. There is an introduction to data analytics techniques with Big Data. Labs and exercises use Python and Apache Spark for data mining with a focus on Business Intelligence and Big Data. Participants will work with a variety of structured and unstructured data sources to model, analyze and visualize data. Upon successful completion of COMP 4254 students will be able to develop an advanced project from start-to-finish which includes data preparation, Business Intelligence and an in-depth analysis on a broad range of data sources.
Prerequisite(s):

• 60% in COMP 2454 and 60% in COMP 2854 and 60% in MATH 3060

​​​This hands-on course is aimed at BCIT Computing students who want to develop and implement an IT project plan. Students focus on Project Management best practices and decisions which apply across the IT sector including software development, building web sites and data analytics systems. COMP 1288 begins with a definition of Project Management fundamentals and terminology. Topics include: stakeholders, scope, deliverables, phases, milestones, deadlines, scheduling, estimates and budgets. Labs and exercises are designed to create project plans that identify and manage risk and take into account quality measures. There is a basic introduction to Microsoft Project software. Participants apply strategies to communicate project progress to stakeholders to keep IT projects on time and on budget. COMP 1288 is an elective in several associate certificates, including Applied Computer Information Systems (ACIS) and Agile Development, and is required for the CST FLEX Diploma. Upon successful completion students will have a basic understanding of project management concepts and tools and will be able to conduct a post project evaluation.
Prerequisite(s):

• No prerequisites are required for this course.

​​​Following on from COMP 2156, and parallel to COMP 3156, this hands-on advanced course was designed for Business Intelligence and Data Analysts. Students who already know how to use Power BI to build and publish reports begin with an in-depth introduction to the dashboard development process. COMP 3157 in-class labs and exercises focus on creating advanced user-friendly reports and dashboards. Topics include visualization best practices, misleading data visualization practices to avoid, how to manage dashboard development projects and more. There is also an in-depth explanation of the Guided Analytics Approach and Dashboard UI/UX principles are also discussed. Labs and assignments include creating advanced reports with Power BI Desktop, identifying common data visualization pitfalls and discussing methods to apply visualization best practices. Participants must provide their own current model PC capable of running Windows 11 and MS Excel, with an i5 or higher equivalent processor, 8 GB minimum RAM, and 256 GB minimum storage. High-speed internet access is needed for online sections and for homework. COMP 3157 is an elective in several BCIT Computing credentials including the CST Diploma (FLEX), and the Applied Data Analytics Certificate (ADAC). By the end of this course, successful students will be able to build innovative and accessible dashboards for various stakeholder groups. This course will be offered in the fall (September) or winter (January) term.
Prerequisite(s):

• 60% in COMP 2156

​This hands-on course has replaced COMP 4678 as of September 2023 and follows on from COMP 1630 and COMP 2364. Students who already understand relational database design, SQL programming and MS Excel are introduced SQL Server Development. SQL Server Development begins with a brief overview cloud computing using the MS Azure ecosystem and MS SQL Server tools. There also will be a brief review of the relational database modelling, Entity Relationship Design (ERD) and normalization topics from COMP 1630. COMP 3678 topics include SQL server data types, the use of Data Definition Language (DDL), and how to write MS SQL queries using Data Manipulation Language (DML). Labs and exercises show how to use SQL Server tools and techniques to optimize SQL queries Transact-SQL (T-SQL) runtime errors. Students will use T-SQL to develop and manage the data layer for software applications, working with relational and portable data from multiple sources in MS SQL Server. Participants will see the basic differences between on premises Database Management Systems (DBMS) and a cloud Database setup. Tasks to Extract, Transform, and Load (ETL) data, MS SQL Server Database operations will also be discussed. ​COMP 3678 is an elective in the Applied Database Administration and Design (ADAD) Associate Certificate, the Applied Data Analytics Certificate (ADAC) and Computer Systems Technology (CST FLEX) Diploma. Successful participants will be able to: manage data from multiple sources, create scripts and database objects using T-SQL. This course will be offered starting April 2024.​
Prerequisite(s):

• 60% in COMP 1630 and 60% in COMP 2364 or 60% in COMP 2362

​This hands-on course follows on from COMP 1630 and COMP 2156. Participants must already understand relational database design, data modeling, SQL programming and the basics of MS PowerBI. COMP 3679 begins with an overview of Business Intelligence (BI) tools and MS Azure data analytics concepts. Students are introduced to cloud computing using Microsoft Azure Cloud Services and explore business intelligence platforms. They review best practices to author, deploy and manage reports using Power BI on Azure. ​Labs and exercises show how to use Azure tools to extract the data from its multiple collections of data sources. MS SQL Server Analysis Services (SSAS) is used to provide additional BI concepts. COMP 3679 topics include BI platforms, the Data Warehouse (DW) Lifecycle and data modelling concepts. Star, Snowflake schemas and using Azure Data on the cloud are discussed. ​There will be a focus on best practices to implement data pipelines and data loading using Azure Data Factory (ADF) and Azure SQL. Various reporting options will be discussed, students will author, deploy and manage significant BI reports. They will extract data from multiple sources, integrated with MS PowerBI. COMP 3679 is an elective in the Applied Database Administration and Design (ADAD) Associate Certificate; the Applied Data Analytics Certificate (ADAC) and the Computer Systems Technology (CST FLEX) Diploma. Upon successful completion, students will be able to use components of the Azure ecosystem to design and optimize Azure data solutions ​for data analysts and developers.
Prerequisite(s):

• 60% in COMP 1630 and 60% in COMP 2156

This online course will provide a comprehensive introduction to the range of accountability and performance measurements approaches used in the Canadian health sector. This course will include the integration of leadership ethics. Accountability systems and processes used across Canada’s provinces and territories will be analyzed and applied. The course will focus on the challenge of providing health services based on unlimited demand but the harsh reality of a fixed capacity of resource. The LEADS Framework will inform the course delivery and learners will be provided with a solid understanding of health leadership application of performance measurement, performance management and governance issues that emerging leaders need to know and apply. *This course will be offered once each year in the winter term as per the annual course schedule.*
Prerequisite(s):

• No prerequisites are required for this course.

This online course will provide a comprehensive introduction to evidence-based decision making in the health sector. The course will examine current practices and protocols, standards of evidence, sources of data, and the application of new knowledge to practice in order to foster change through health sector initiatives and projects. The course will include reference to the underlying ethics of decision making evidence. Critical thinking and analysis activities will be applied throughout the course and the LEADS Framework will inform the course delivery. *This course will be offered once each year in the Spring term as per the annual course schedule.*
Prerequisite(s):

• No prerequisites are required for this course.

​Acquiring effective communication and presentation skills will help advance your career and bring positive attention to your projects and ideas. In this course, you will review sample speeches, perform audience and purpose analysis for your own project, rehearse effective public speaking techniques, and deliver your final presentation to a wider audience. Students can present on a school project from one of their technical courses, an entrepreneurial idea, or a current work project.
Prerequisite(s):

• No prerequisites are required for this course.