Integrate: Automated Data Pipelines & Data Warehouses

Plaid offers a variety of automated data pipeline and warehouse packages designed to make your reporting & analytics life simpler. Working with the major Student Information Systems and integrations with a variety of systems surrounding them, we help you scale your reporting and analytics capabilities fast.

Our technology expertise includes; Banner, Colleague, PeopleSoft, Workday, numerous home-built systems; Microsoft Dynamics, Salesforce, and other CRMs; and of course modern cloud platforms like Amazon Web Services and Microsoft Azure. We'll even ingest your spreadsheets so you can have a single source of truth.

  • Accurate enrolment reporting
  • Metrics to support your decision-making, from Full-Time Equivalent to diversity, equity, and inclusion, classroom utilization, outcome assessments, performance, revenue, applicant diversity, longitudinal cohort analysis and many more.

Analyze: Strategic, Tactical, & Operational Dashboards

Plaid Analyze is a subscription service consisting of strategic, tactical, and operational dashboards designed for strategic enrolment management professionals helping institutions meet their SEM goals and allows institutions minimize the cost of building dashboards. This includes a service level agrement of monthly dashboard improvements, access to online training, one new dashboard per fiscal quarter, and a quarterly dashboard check-in with one of Plaid's SEM experts.

  • Reduce manual data pulls: Automate dashboard updates to refocus time spent.
  • Shift focus: Shift your analysts to focusing on the why? instead of the what with dashboards that update automatically.
  • Interactive dashboards for all stakeholders: Understand the high-level trends, and drill into the detail.
  • Better support underrepresented groups: Group your data by demographics, such as ethnicity or Indigenous status to identify opportunities for student success supports.
  • Optimize enrolment: Track how class enrolment has changed by modality and optimize opportunities for students and faculty.

Forecast: Enrolment & Tuition Forecasting

Enrolment executives are facing increasing pressure to hit strategic enrolment and budgetary targets, and maximize growth. Many enrolment executives struggle to create accurate and timely forecasts of student enrolment revenues due to a lack of people, time and tools. The current pandemic has highlighted just how fragmented existing forecasting processes are. To address this challenge, Plaid has developed Plaid's forecasting tool Forecast – the first web-based enrolment forecasting platform modelled exclusively for higher education.

Plaid's Forecast aligns academic and financial planning teams whilst eliminating bottlenecks in the forecasting process. By producing timely and accurate enrolments forecasts, Plaid's Forecast enables data-informed insights and decisions that help enrolment executives:

Plaid's Forecast provides a faster and more scalable enrolment forecasting platform compared to traditional alternatives which are less intuitive, more difficult to use and prone to human error. In addition, Plaid's Forecast provides full audit capabilities, delivering greater governance and collaborative functions that are not present in alternative solutions.

Working with Andrew and Pat from Plaid Analytics has been a pleasure. Plaid helped Postgraduate Medical Education at UBC transition from a spreadsheet based workforce planning system to a dedicated forecasting system which is accurate, intuitive and state of the art. It has transformed our operations and enables us to forecast much more accurately on the number of residents in each of our programs. This is of great benefit to our workforce and financial planning. Plaid are experts and market leaders in their field. They are passionate about what they do and both professional and attentive to our needs. Plaid have unique insights and they continue to support us with their expertise.

Rob Brackenbury | Senior Manager, Postgraduate Medical Education Faculty of Medicine, The University of British Columbia

Govern: Data Governance

Plaid's data governance tool Govern is a cloud-based metadata management tool Plaid modelled expressly for higher education institutions to better understand and utilize their data. Plaid's Govern is a cloud-based platform with data search and discovery schemas, traceable lineage between cloud-based and on-premise systems, defined data governance roles, and circumscribed user access permissions. Plaid's Govern facilitates thorough documentation by way of tags, business glossaries, visual data lineage across multiple systems, as well as ownership and usage information.

Implementing Plaid's Govern supports the data governance initiatives of higher education institutions by centralizing data definitions and glossaries, making data lineages transparent and accessible, and facilitating impact analysis so that any downstream impacts of changes are minimized. There are managed and open-source options available, creating the opportunity for continuous innovation – Plaid's Govern is committed to offering feature releases. Plaid's Govern allows for integration to various campus and vendor systems - if an integration doesn't exist, Govern's flexibility allows for custom development. This metadata tool helps users understand where data comes from, thereby promoting trust in the data origins.

In my experience, learning a new skill is easier when the topic and training is in context to our work. When the choice for Tableau training was to work with sales data or higher education data, the decision to work with Plaid was an obvious one. I could not have hoped for a better experience for my team.

Jodi Magee | Director, Institutional Research & Planning - Queen's University

Collaborative Process

Data governance is a collaborative process to help your institution treat your data as an asset.

Data Definitions

Data definitions allow all stakeholders to share a common understanding of data and terms.

Data Lineage

Data lineage allows your team to both investigate where data comes from, but also identify where making changes could cause downstream negative effects.