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: COMP 1002 or equivalent knowledge of a Windows PC and file management.

This advanced course builds on top of COMP 2010, and assumes prior knowledge of Excel fundamentals. Starting from an intermediate level, students learn to create meaningful spreadsheets that can be used to analyze, communicate and manage information. This instructor lead, hands-on course provides lectures, lab exercises and assignments that are designed to provide practical skills. Advanced topics include: consolidating data in multiple worksheets templates, dealing with error messages, solver and macros. There will be a review of sub-totalling and pivot tables taught in COMP 1362. Participants progress to expert in just 6 weeks. Only those students who have completed COMP 2010 and who have self studied all of the topics in COMP 1362 should register for this advanced level course. Prerequisite: COMP 1362 or COMP 2010 or equivalent knowledge.

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: Math 12 Pre-Calculus or equivalent

This course is aimed at BCIT Computing and Business students. Participants will review the laws and regulations that apply to the Internet and information technology.They also look at how to engage intellectual property rights, law and regulation to protect intellectual effort. Topics include privacy, private data collection, property (IP/DRM), security, gambling, ethics, and the internet of things/everything (IoT). Data, patents, trademarks, domain names, copyright, linking, meta-tags, online contracts, online advertising and marketing will also be discussed. Students receive an overview of law in the modern marketplace, via a series of non-cumulative exercises, and a role play exercise.

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. Prerequisite: COMP 1002 or equivalent knowledge, plus a working knowledge of MS Excel. We recommend that students working toward a Computing credential complete COMP 1630 first.

​Business Analysis and Systems Design is the study of concepts, processes and tools that professionals use to plan and develop computer information systems to industry standards. COMP 2831 continues the established Systems Analysis tradition and provides the foundation for all BCIT Computing development credentials. Students learn how to ask implicit questions, to create and document communication plans and to make better decisions prior to creating an information system. Beginning with an introduction to the SDLC, Software Development Life Cycle, students work in teams to initiate the system process, analyze problems, discover requirements and create a logical design. 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. Agile frameworks including XP, Extreme Programming, and SCRUM are also introduced. Students learn to work in groups to provide detailed written materials and make presentations of their designs. By the end of this course, successful participants will be able to use industry standard tools and methods to analyze, design, and implement information systems. This course is deemed equivalent to the full-time diploma courses COMP1712 and ACIT2831 Students who complete COMP 2831 will be prepared to move on to COMP 2833 Agile Software Development with Scrum and the Agile Development Associate Certificate. Prerequisite: COMP 1630 or COMP 1409 or equivalent knowledge, plus the ability to work in groups and to communicate in business English.

This hands-on course follows on from COMP 1630, COMP 2362 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. Prerequisites: COMP 1630, COMP 2362 and MATH 1060.

Continuing on from COMP 1630 this workshop is a primer on business intelligence, data warehouse and data analytics for those moving on to higher level courses. Students must already understand industry standards in data modeling, relational database design and creating reports with SQL. This weekend workshop provides an overview of data warehouse planning and design for those moving on to the specific Business Intelligence Analytic tools covered in: COMP 4679, COMP 4680 and COMP 4681. Topics include: an overview of business intelligence the role of Extract, Transform and Load (ETL) in the data warehouse, the typical data warehouse lifecycle, plus an introduction to dimensional modeling for data warehousing. Labs focus on ETL, data quality considerations, and dimensional modeling concepts including the star and snowflake schemas. Successful participants will have an understanding of Business Intelligence concepts and industry standards in data design for data structures for information systems. Prerequisite: COMP 1630 or equivalent knowledge of data modeling and SQL.

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: COMP 1002 or equivalent knowledge.

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, COMP 4680 and COMP 4681. Prerequisites: COMP 1630

Apache Hadoop is the open-source framework designed to help solve some of the storage and analysis issues around Big Data. This hands-on workshop continues on from COMP1630, and assumes prior knowledge of the industry standards in data modeling, relational database design, and SQL programming. It is aimed at a broad audience including administrators, data analysts, and managers. Participants build on their existing database skills to work with larger and more complex data sets and to gain an overview of Hadoop and Big Data. Starting with the basic concepts and components of Hadoop, students will use Hive to query data stored in Hadoop with an SQL-like query language. Lectures and labs introduce the normal usage of a Hadoop system using the Cloudera Quickstart virtual machine. Homework and exercises will focus on getting data into the Hadoop Distributed File System (HDFS), basic file operations, and running queries on existing data. Upon successful completion of this course, participants will be able to define Big Data, identify the basic components of Hadoop, and run queries on Big Data using SQL on Hive. Prerequisites: COMP 1630

In order to register in COMP 4254 students must have completed all prerequisites. This is the final course for the Applied Data Analytics Certificate (ADAC) from BCIT Computing. Students are encouraged to take MATH 3060 prior to this course, or concurrently. Building on statistics, data mining, and visualization techniques, students who have completed the core requirements of ADAC will be able to integrate these advanced topics into a data analytics project. Participants are introduced to emerging xamines sources of digital mapping data, data standards, mapping compilation procedures, mapping systems, and an introduction to cartography.tools and techniques in data analytics and Big Data. Labs and exercises use Excel, Python and Apache Spark for data mining with a focus on Business Intelligence and Big Data. Discussions also include NoSQL databases, and Hadoop. Students learn to work with a variety of structured and unstructured data sources to model, analyze and visualize data. Upon successful completion, participants will be able to present an advanced data analytics project start-to-finish. This course will be offered in the Winter (January) and Fall (September) terms.

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 the Applied Data Analytics Certificate offered by BCIT Computing. Prerequisite: MATH 1060 or equivalent.

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: A post-secondary Communication or English course or equivalent.

User Experience (UX) encompasses a wide range of activities including User Interface (UI) design, Information Architecture (IA) and field research. Usability design and testing, tight integration and collaboration with software development processes are included in UX. This hands-on course is an introduction to UX/UI for those who are creating user interfaces for web sites, mobile applications, and information systems, as well as those who want a better understanding of the role of UX/UI. Students will follow an iterative and agile approach focusing on User-Centered Design (UCD) as the motivator for product direction. Skills learned in this course will apply to web and mobile applications as well as IT systems interface development. Participants will be expected to work within interdisciplinary teams, with emphasis on collaboration, brainstorming, and continued evolution of an interface concept based on UCD. Upon completion, successful students will be able to incorporate user-centered iterative design principles and processes into a wide variety of IT projects. Some students may want to complete COMP 1910 – Introduction to 3D Simulations and VR/AR concurrently with COMP 1011. Prerequisite: COMP 1002 or equivalent knowledge of using a Windows PC and file management.

This hands-on course is aimed at BCIT Computing students who want to learn how to develop and implement an IT project plan. Project Management best practices and decisions apply across various IT sectors including: Web and Software Development, Databases and Networking. Topics include: identifying project stakeholders and defining roles and responsibilities of the team, defining scope, devising risks and quality plans, mapping-out a schedule, determining a budget and defining a communication strategy. Participants are introduced to the Microsoft Project software application. Students receive an overview of common project management concepts which they can apply to real world IT projects on time and on budget. Prerequisite: COMP 1002 or equivalent knowledge of a Windows PC, and file management.

This hands-on course follows on from COMP 1850 and COMP 2015 or those who already understand scripting with HTML, CSS, JavaScript and jQuery. Students are shown how to use web analytics software such as Google Analytics and Google Optimize to gain a better understanding of users' journey across a website and connected digital properties. Google Tag Manager is used to collect clean and reliable web data in Google Analytics. Participants generate various analytics reports and dashboards in Google Analytics and Google Data Studio to analyze web data to improve user experience and website usability. Labs and exercises are designed to reinforce best practices for digital data collection through real case-studies in complex web ecosystems. Topics include: Develop and implement web data collection procedures in Google Analytics using Google Tag Manager, testing and experients using Google Optimize, survey and Heatmap tools, data analysis tools and techniques using dashboards, custom reports and segmentation. Students will examine opportunities for continued website improvement and learn how to optimize web pages for better traffic acquisition. By the end of this course successful participants will be able to collect reliable and actionable web data in Google Analytics using Google Tag Manager for continuous website usability improvement. COMP 2251 will be offered once a year in the fall term. Prerequisite: COMP 1850 and COMP 2015 or equivalent knowledge of HTML5, CSS3, JavaScript and jQuery.

Crystal Reports is a cost effective business intelligence application provided by SAP for small businesses. It has a very large install base and it is used to design and generate reports from a wide variety of data sources. Students are first introduced how to plan Crystal Reports designs and then how to develop basic business intelligence reports. After the mid-term they learn to apply best practices for enhanced report design. Participants learn how extract and manipulate data, saving time to develop automated and custom reports. By the end of this course, successful participants will know how to use Crystal Reports to produce a variety of different charts and multiple ways to depict data. COMP 2252 is an elective in the Applied Computer Applications (ACA), and the Applied Database Administration and Design (ADAD) Associate Certificates, as well as the Applied Data Analytics Certificate (ADAC) and the CST/PTS Diploma. Please note: COMP 2252 will only be offered in the January and September terms. Prerequisite: COMP 1002 and COMP 2010; or equivalent understanding of MS Windows and Office.

​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: COMP 1630 or equivalent knowledge.

​Following on from COMP 1630 and COMP 3838, this course is for students who already understand relational database design, data modelling, SQL programming and data warehouse foundations for business intelligence. Participants are provided with an in-depth understanding of authoring, managing and delivering traditional and interactive reports using Microsoft SQL Server 2016 Reporting Services (SSRS). 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 an overview of Microsoft SQL Server 2016 Analysis and Integration Services, which provides additional business intelligence architecture concepts and some preparation towards the Microsoft certification exams. Successful participants will learn to extract the data from its multiple collections of applications and data sources, how to deliver and manage reports, to integrate SSRS reports and apply best practices for reports authoring, deployment and management. Please note: COMP 4679 will be offered in the Spring (April) and Fall (September) terms. Prerequisites: COMP 1630 and COMP 3838

This advanced course follows on from COMP 4677 and is designed for those who already understand relational database design, data modelling, SQL programming and MS SQL Server Administration but have little or no extract, transform, and load (ETL) experience. The course will cover ETL fundamentals, SQL Server Integration Services (SSIS) tools, and SSIS package development. Students will use Business Intelligence Development Studio (BIDS) in the lectures and labs to work with control flows, data flows, variables, package configuration and deployment, security, troubleshooting, logging and tuning. Students will also be introduced to ETL for the data warehouse. This course also helps to prepare for the SSIS component of the Microsoft Certified Technology Specialist (MCTS): Business Intelligence Developer, which is available through third parties for additional fees. Successful participants will gain a deeper understanding of ETL and Business Intelligence using Microsoft tools. Please note: COMP 4680 will be offered in the fall term only. Prerequisites: COMP 4677

​Following on from COMP 1630 and COMP 3838, this course is for students who already understand relational database design, data modelling, SQL programming and data warehouse foundations for business intelligence. This hands-on course is designed to provide an introduction to Microsoft SQL Server Analysis Services (SSAS) for online analytical processing (OLAP) and data mining for business intelligence applications using Microsoft Tools for data mining. Microsoft SQL Server 2016 and MS Excel are used to design, create and manage multidimensional structures containing data from other sources such as a relational database. Focusing on the role of SSAS, participants are shown how to create and maintain an Analysis Services database. They will learn to use data mining techniques to extract data from collections of multiple data sources and applications. Topics include: Designing Multidimensional Business Intelligence Semantic Model (BISM), Accessing different data sources, Creation of multidimensional databases, Data mining, interacting with cube data using Multidimensional Expressions (MDX) queries and from MS Excel. Aggregation, conversion, Drillthrough and Writeback are also discussed. This course also helps to provide some preparation for the SSAS component of the Microsoft certification exams. Upon completion of this course, successful participants will be able to use SSAS to deploy an Analysis Services database with multiple levels of security for data mining. Please note: COMP 4681 will be offered in the Winter (January) and Fall (September) terms. Prerequisites: COMP 1630 and COMP 3838

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.*

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.*