- ETL (Extract Transform Load)
We provide ETL services to create enterprise wide reporting and analysis datasets in our Data Warehouse. The datasets are accessed using many different reporting and analysis tools. ETL processes are used to batch load data from enterprise systems such as Financials, Student Records, Payroll, eResearch, and DART. Our team ensures the data is accurate and available using several ETL tools, including Informatica, SQL Server Integration Services and SQL Server Analysis Services. As systems are upgraded or changed, we have an important role in ensuring information integrity. We offer consultation services using tools, insuring data consistency and migrating data between software systems on a one time basis.
- Data Integration Services
We support API (Application Program Interface) development platforms for real time consumption of data in a securely managed environment. IQ administers the API Directory and offers assistance with creation of new APIs. We are working with the medical campus and MCIT to implement the new IBM API Manager tool. We also support custom integrations to customers, such as providing the bridge between Common App and ImageNow. This enables them to convert, combine, store and view student applications integrated into their existing workflow. Another example is providing integration between College of Engineering Flux Services with reporting and billing applications.
?We provide business analytics applications to diverse customer base including eResearch, Financial, Schools and Colleges and ITS Internal. This gives university management and research leaders an accessible, easy-to-use, web-based reporting tool that facilitates efficient analysis of financial, student, human resources data and more to foster data-driven decisions. M-Reports delivers the management reports you need in a customizable user interface.
IQ Coordinates BusinessObjects system administration, build and maintain universes, as well as answer customer questions.
We support Tableau by overseeing system administration, training and customer assistance.
- Data Architecture
We deliver data models, Data Fit-gap Analysis and Design, Reverse Engineer Physical Database.
Data Concierge Pilot
Previously, requests for administrative data were handled inconsistently: it sometimes took months to fulfill them, and requesters were not always kept informed of progress. Data Concierge aims to create a one-stop shop for university data needs.
The Data Concierge pilot provides a way to obtain administrative and learning management data in a consistent, timely, and secure manner in close collaboration with data owners and subject matter experts. During the pilot, you can continue using existing channels to request administrative and learning management data. Requests routed to Information and Technology Services (ITS) will now be captured and managed via an efficient and transparent process providing:
- A central point of coordination
- Consistent authorization checks and data steward approvals
- Timely updates on request status and progress
Data Concierge is key to creating an unparalleled IT environment at U-M that supports the university’s teaching, learning, and research activities. It will help U-M administrators better meet the changing operational needs of the university, reduce costs, and improve efficiency. Long-term, it may expand to fulfill academic and research data needs as well. If you have questions or suggestions for improving Data Concierge, please contact IQ. We would love to hear from you!
Some Projects We Support
- Student Explorer integration with Canvas
The University of Michigan began piloting Canvas as a replacement Learning Management System for CTools in September 2014. The IQ team integrated Canvas into the existing LMS data flows without any interruption to the analytics data. The existing data set is critical to Student Explorer, an early warning system used by advisers in LSA and other units and an early example of learning analytics work manifesting itself as actionable intelligence. (Customer contacts are Kris Steinhoff & Rachel Neimer at DEI.)
As learning analytics has matured at the University of Michigan, scholars have recognized the opportunities afforded by the availability of rich student data. The LARC (Learning Analytics Data ARChitecture) data set will aggregate nearly 300,000 student portraits in a format targeted for researchers. LARC will feature student records and admissions data, but also may grow to include other areas of interest, such as housing and instructor demographics.
IQ is representing the University of Michigan on multiple Unizin and Canvas analytics task forces and working groups, advocating for the university’s needs and contributing back to the community.
- M-Pathways Financials & Physical Resources System upgrade to version 9.2
IQ has participated on the ITS FIN Upgrade Project team for the duration of the project. We have partnered with the team to assess and implement necessary Data Warehouse modifications deemed necessary. The project included updates to both PeopleSoft and Oracle software systems, as well as a new hardware platform. Additional effort has been allocated to assess performance given the new operating environment.
Our Growth Areas
We are venturing into exciting new areas. In the coming months we plan to:
- Build a "master dashboard" of key institutional data for President Schlissel
- Work with stewards and subject matter experts to develop additional dashboards for U-M leadership.
- Support library analytics, customer/constituent relationship management (CRM) analytics, and high-performance computing to build competence and add value in those areas.
- Collaborate with Digital Education and Innovation and the ITS Teaching and Learning team to build a data virtualization platform that provides a single, logical view of all academic data.
- Engage with business intelligence teams across U-M, including Michigan Medicine, to minimize redundancy.
- Partner with our central finance leadership team to create a financial model for Tableau as a common good service.