Project DTB: Dashboards for Teaching Business Intelligence
Centre de Recherche Créatech sur les Organisations Intelligentes
Dashboard applications are increasingly used in businesses to monitor processes and performance. However, dashboard design poses great challenges to IT and business professionals. The transition from spreadsheet data visualisation to full- blow dashboard creation and sharing platforms has proven to be difficult in many organizations.
The Centre de Recherche Créatech sur les Organisations Intelligentes is a research center at Université de Sherbrooke that focuses on the use of data and information to improve the performance of organizations. This project is an initiative of Pr. Daniel Chamberland-Tremblay.
Pr. Chamberland-Tremblay teaches Business Technology Management and Business Intelligence at École de gestion at Université de Sherbrooke. His research interests include data management, data governance, data security and the data-based value creation process.
Well-designed visual data products tend to be the exception on the Web. Moreover, data product design books tend to focus on one visual aspect at a time or on very few integrated examples, such as dashboards, that it leaves the learner with many tools but very few good examples to be inspired by.
Objectives and limits
The main objective of this project is to develop a set of annotated business dashboard references and bloopers to support teaching in the field of business intelligence. More specifically, the project goals are:
- Develop a set of annotated business dashboard for different lines of business. The dashboards should be presented in the context of reference conceptual framework, like the Monitoring-Analysis-Details (MAD) framework.
- Document the business dashboard according to its intended use, data visualization best practices and other conceptual frameworks.
- Create or use sample data. If possible, data from Project BDS (A Business Data Simulator for Teaching and Research) should be used.
This project uses the open-source MIKE2.0 (Method for an Integrated Knowledge Environment).
MIKE2.0 is an open-source methodology for Enterprise Information Management that provides a framework for iterative information development. The main goals are:
- Driving an overall approach through an organization's Information Strategy
- Enabling people with the right skills to build and manage new information systems while creating a culture of information excellence
- Moving to a new organisational model that delivers an improved information management competency
- Improving processes around information compliance, policies, practices, and measurement
- Delivering contemporary technology solutions that meet the needs of highly federated organizations
Information development starts with the assessment of the organizational business and technological contexts. Combined with the organizational information objectives, theses phases result in a gap analysis that details priorities for the implementation phases. The iterative nature of information development ensures that information resources are developed in an incremental manner that fits the evolving organizational needs.
As the project progresses, steps can be added, modified, or removed to improve the different aspects of data management from data identification and collection to data preparation and analysis.
This project will rely on well-established Python libraries like Plotly Dash or business dashboarding applications like PowerBI.
Dash is the most downloaded, trusted Python framework for building ML & data science web apps.
PowerBI is the Microsoft dashboarding and data visualisation application. The project will be hosted on GitHub.
The iterative nature of the project warrants for a regular monitoring. Typically, students are expected to present their progress every week, or every two weeks, in short briefings similar to Scrum stand-up meetings. During these meetings, the student will be asked to report on the work done, on the tasks to come and on the issues blocking progress.
Students can also contact the supervisor through email or Teams at any time to resolve blocking issues.
This project can be designed to fit internships ranging from 45h to 225h, or event more. Given the exact availability of the candidate, the project can be limited to few business examples or be expanded to a full-blown BI business case.
The project is divided in five stages:
Stage 1: Project setup and kickoff
This stage is dedicated to the installation of the project technological environment, including Python, Dash and their dependencies and PowerBI. Functional tests to ensure the adequate behavior of the components will be carried out. During this stage, the candidate will be required to familiarise his or herself with the basics of each framework and applications.
Stage 2: Building a basic example
At this stage, the candidate will build a basic dashboard example from a standardized data. Deliverables include the proof-of-concept dashboard and a model of the dashboard process creation.
Stage 3: Scaling the dashboard
This stage is dedicated to expanding the portfolio of dashboards to different business functions, processes and activities in a manner that enables further development. Deliverables include the dashboards and the analyses of the design. This stage can be scaled up or down depending on the internship duration by adding new decision contexts or limit the scope to a few business activities.
Stage 4: Creating a full-blown business case for data analytics (optional stage)
If the candidate reaches a substantial set of dashboard examples within a reasonable timeframe of the internship, the creation of a business case will be encouraged.
Stage 5: Reporting on the project
The last, but mandatory, stage is project reporting. The candidate will be asked to package all development in a manner that supports reuse by others. A short project report will also be required before the completion of the internship.
The salary for the internship ranges from 18$/h to 22$/h depending on experience and skills.
The internship candidate should be a graduate student knowledgeable in Python, SQL and basic Web development. A basic knowledge of the language SQL would be an asset.
Candidates that want to know more about this project or that wish to apply should contact Pr. Chamberland-Tremblay through email at daniel.chamberland- firstname.lastname@example.org.