Applied Data Analytics

This intensive, hands-on course is the prerequisite for all advanced database courses in BCIT Computing programs. COMP 1630 is equivalent to the Full-time CST and CIT Diploma database courses and provides an introduction to relational database design concepts and industry standards. Students learn the tools and processes for data modeling in Relational Database Management Systems (RDBMS) in a Windows PC lab environment. They also 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, object-relational DBMS, data warehousing, OLAP- online analytical processing and database uses web technology are discussed. Students in COMP 1630 are required to attend one face to face meeting each week, participate in group work, and an online component, plus complete reading and assignments outside of class. 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: Data Warehouse, Data Quality, MySQL, MS Business Intelligence, MS SQL Server and Oracle.
Prerequisite(s):

• 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 follows on from COMP 1630 and was designed to introduce Python as a tool for data analytics. Students must have prior database systems and Structured Query Language (SQL) programming, plus have basic Excel spreadsheets skills before registering for this course. Participants must provide their own current model PC with a minimum of an i5 or equivalent processor, 8 GB of RAM and 256 GB storage capable of running Windows 10 or above. High-speed internet access is needed for online sections and homework. BCIT does not provide technical support for student's hardware or operating systems. Starting with an overview of the Python IDE, participants will explore foundational Python programming concepts. Participants are introduced to Variables, Conditions, Operators, Loops, Functions, Arrays, Dictionaries and DataFrames. Exercises and labs explore data analysis using simple statistics with Python. Students are also introduced to string manipulation, Regression, Aggregation, and object-oriented structures with Python used in data analysis. Students are shown how to use Python for basic graphing. COMP 2454 is a required course in the Applied Data Analytics Certificate, ADAC from BCIT Computing. Upon completion successful students will use Python to perform exploratory data analysis and as preparation for data modeling.
Prerequisite(s):

• 60% in COMP 1630

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.

​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

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 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 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 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 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. 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 will use a variety of technologies and will learn about different big data systems including AWS Academy Data Analytics. Students conduct a big data analysis with practical, real-world examples and focus on how to analyze vast data sets using a case-study approach. Topics include an overview of different data stores, querying data with visualizations, and a deep-dive of Extract, Transform and Load (ETL) process in the data warehouse. BCIT Computing is an AWS Academy partner; A discount voucher for the AWS Certified Data Analytics–Specialty exam will be provided to those who pass this course. 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. MATH 3060 will be offered only in the fall (September) and winter (January) terms.
Prerequisite(s):

• 60% in MATH 1060

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.

IT security is growing area with several domains including both information security and network security. This course replaces COMP 3705 which covered both information security and network security. COMP 3704 will provide a more in depth overview of key topics in information security only and is one of the prerequisites for COMP 4704 Applied Network Security. IT professionals across multiple sectors from software development, database, web, mobile and networks will benefit from the material covered.  This hands-on course is led by local industry experts who will share their knowledge and best practices for securing computer systems. Students will complete labs and exercises to experience applied IT security and gain a practical knowledge. Topics will include: security awareness, risk mitigation and control administration, data and application security, cryptography, attack techniques, penetration testing, vulnerability assessment, incident response, disaster recovery, and forensic analysis. In addition, information handling best practices, privacy and regulatory issues are discussed. Upon completion of this course, successful participants will be aware of best practices in IT security and how to implement secure information systems. Network related aspects of IT security are covered in the follow-on course, COMP 4704 “Applied Network Security".
Prerequisite(s):

• 60% in COMP 1002

Continuing on from COMP 1630 this course is aimed at students who already understand relational database, data modeling and the importance of improving Data Quality (DQ). Survey topics include the business impact of DQ, data profiling techniques, DQ capability/maturity models, Data Governance, DQ improvement roadmaps and approaches to gaining executive support for the DQ improvement program. In class labs, homework assignments and a project focus on how to use Data Quality techniques and tools. Successful participants learn how to apply a data quality framework to data migration projects and are better prepared to move on to the specific Business Intelligence Analytic tools covered in: COMP 4679 and COMP 4681.
Prerequisite(s):

• 60% in COMP 1630

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 and students can expect a minimum of 3 hours per week online in real time via the BCIT Learning Hub plus using two-way audio and video. 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. This course will be offered in the Winter (January) and Spring (April) terms.
Prerequisite(s):

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

​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.

This hands-on introduction to UX/UI is aimed at those who want to experience the development of user interfaces for applications, web sites, mobile applications, and information systems. COMP 1011 follows an iterative and agile approach focusing on User-Centered Design (UCD) as the motivator for product direction. Participants are expected to work within interdisciplinary teams, there will be an emphasis on collaboration, brainstorming, and the continued evolution of an interface concept based on UCD. User Experience (UX) encompasses a wide range of activities including User Interface (UI) design, Information Architecture (IA) and user research. Usability design and testing, tight integration and collaboration with software development processes are included in UX. COMP 1011 is required in the Computer Systems Certificate, CSC and is an elective in several other Computing programs. Upon completion, successful students will be able to incorporate user-centered iterative design principles and processes into a wide variety of IT projects.
Prerequisite(s):

• 60% in COMP 2831 or 60% in COMP 2501 or 60% in COMP 2132

​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 the Applied Computer Information Systems, ACIS and Agile Development Associate Certificates, it is required for the CST/PTS Diploma. Upon successful completion students will have an introduction to project management concepts and be able to conduct a post project evaluation.
Prerequisite(s):

• COMP 1002

Crystal Reports by SAP is a low-code reporting solution used to create reports and dashboards from a wide variety of data sources, with minimal coding for Business Intelligence (BI). Students who know how to use a Windows PC and MS Office are introduced to planning and developing business intelligence reports. COMP 2252 participants will create dynamic reports and dashboards. Labs and exercises apply best practices in: report design, how to extract and manipulate data, and display information in custom formats from many sources. COMP 2252 is an elective in Applied Computer Applications (ACA); Applied Computer Information Systems (ACIS); Applied Database Administration and Design (ADAD) Associate Certificates, as well as the Applied Data Analytics Certificate (ADAC) and the Computer Systems Technology (CST/PTS) Diploma. Please note: This course will be offered in the January (Winter) and September (Fall) terms. By the end of this course, successful students will be able to use Crystal Reports to display and analyze data visually for BI and to make actionable decisions.
Prerequisite(s):

• 60% in COMP 2010 or 60% in COMP 2364

​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 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 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.
Prerequisite(s):

• 60% in COMP 2156

​Following on from COMP 1630, students who already understand data modeling, relational database design and SQL are provided with an in-depth understanding of designing and implementing MS SQL 2016 Server databases advanced T-SQL and scripting methods. There is an overview of BI tools (MS SQL Server Reporting Services, MS SQL Server Integration Services) and comparisons between different editions of MS SQL Server. Topics include: architecture, new SQL 2016 components, T-SQL review, new T-SQL constructs for SQL Server 2016, programmable objects, security for the database developer and performance tuning procedures. Exercises and labs help students obtain a thorough understanding of Microsoft SQL Server 2016 from a database developer perspective, with a focus on how to create views, stored procedures and triggers. Successful participants will be able use procedural code in TSQL and .NET to develop and manage the data layer for software applications. Please note: COMP 4678 will be offered in the winter (January) and fall (September) terms.
Prerequisite(s):

• 60% in COMP 1630

​This hands-on course follows on from COMP 1630. Students who already understand relational database design, SQL programming are introduced to SQL Server Reporting Services SSRS. Students 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. Please note: BCIT does not provide technical support for student's hardware or operating systems. COMP 4679 topics include how to install, configure and manage SSRS; author reports using SQL Server Data Tools (SSDT), and apply multiple levels of report security. Students receive a brief overview of Microsoft SQL Server Analysis Services which provides additional BI concepts. Labs and exercises show how to use SSRS to extract the data from its multiple collections of applications and data sources, how to deliver and manage reports, to integrate SSRS reports. Participants explore business intelligence platforms and apply best practices to author, deploy and manage reports with SSRS. COMP 4679 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/PTS Diploma. Participation online via the BCIT Learning Hub and attendance are mandatory during scheduled class hours plus online activities for a minimum of 4 hours per week. Students should also plan for 9+ hours reading and homework each week. Upon successful completion of COMP 4679 students will be able to use SSRS to deploy a Reporting Services database, they will be able to extract data from multiple data sources and integrate traditional and interactive SSRS reports. Please note: COMP 4679 will be offered in the Spring (April) and Fall (September) terms.
Prerequisite(s):

• 60% in COMP 1630

This hands-on course follows on from COMP 1630. Students who already understand relational database design, SQL programming and data warehouse foundations are introduced to SSIS. COMP 4681 is a blended BYOD course, participants must provide their own Windows 10 dual core laptop with a minimum of 8GB RAM to participate in this course. Please note: BCIT does not provide technical support for student's hardware or operating systems. Topics include: how to install, configure and manage SSAS; designing multidimensional Business Intelligence Semantic Model (BISM), accessing different data sources, creating multidimensional databases, data mining, interacting with cube data using Multidimensional Expressions (MDX) queries from MS Excel. Labs and exercises show how to use SSAS to design, create and manage multidimensional structures containing data from other sources. Participants are shown how to create and maintain an Analysis Services database. MS Excel and MS SQL Reporting Services are used to present data from SSAS. COMP 4681 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/PTS Diploma. Participation online via the BCIT Learning Hub and attendance are mandatory during scheduled class hours plus online activities for a minimum of 4 hours per week. Students should also plan for 9+ hours reading and homework each week. Please note: COMP 4681 will be offered in the winter (January) and fall (September) terms. Upon successful completion of COMP 4681 students will be able to use SSAS to deploy an Analysis Services database with multiple levels of security for data mining, they will be able to extract data from collections of multiple data sources and applications.
Prerequisite(s):

• 60% in COMP 1630

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.