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Colleague Connection: Champions of Data

In the University’s quest to enhance data-driven decision-making, the Data Management and Analytics (DMA) team uses its expertise to organize and provide access to data that enables business units across campus to uncover patterns, predict trends, and extract meaningful insights to drive strategic decisions and operational efficiencies. Alan Garbarino, director of Data Management and Analytics, offers an insight into how his team of data champions plays a pivotal role in shaping the future of success at Northwestern.

What is the role of DMA?

DMA is a unit within Administrative Systems. We develop and support data sets, self-service interfaces, and institutional reporting for Northwestern enterprise systems. DMA maintains the University Business Intelligence platform (Cognos) and the Tableau visualization platform. The team also negotiates and manages Northwestern licensing for Tableau Creator and PowerBI toolsets.

Three working groups in DMA collaborate closely to support analytics needs across the University.

Data Analysts

The Data Analysts possess a deep understanding of various data management processes and requirements, including security and documentation concerns. When a business partner requests data, this group is the first to engage, connecting with them to comprehend and define their business needs. They then document these requirements, setting the stage for the development work that follows.

ETL Developers

Once the requirements are established, the ETL (Extract, Transform, Load) Developers take the lead. They design and develop data flows and data warehouse structures that precisely meet those requirements. The team utilizes a tool that enables us to connect to source applications, extract data, and place it into the data warehouse. During this process, we transform the data to ensure it is efficient for reporting and to develop value-added metrics.

Business Intelligence Developers

Then, it is the responsibility of the Business Intelligence Developers to take the data warehouse structures created by the ETL developers and build self-service interfaces or APIs or create Cognos reports that the Northwestern community can use to access that data.

Because of the wide variety of areas that we support, requests for data can come from anyone, from a distributed IT group in Kellogg that requests an API to access information from the data warehouse to a central office that is looking for greater insight into how day-to-day transactions are allocated within their area to understand process efficiency and help with future organizational planning.

How does DMA ensure data quality and integrity in large datasets?

Data integrity is critical to ensuring the accuracy of the data warehouse information the University relies upon for decision-making. The DMA team monitors daily data flows to ensure batch integrations run error-free and to research any discrepancies in those jobs.

In addition, many automated validation processes compare row counts and aggregate hash totals for key data elements to ensure that data warehouse data is consistent with source system data.

How do DMA's services impact the University's decision-making?

Cognos data sets and dashboards, data warehouse reports, and self-service reporting functions support many University business functions, including Financial Operations, Research Administration, Alumni Relations and Development, Human Resources, Student Affairs, and Facilities.

These DMA products support decision-making across the University in many ways. Some examples are:
  • Finance and Procurement reports are used by schools and units to monitor financial health.
  • Student reports are used to access course evaluation data for planning and to provide information to understand and optimize the student experience across a wide range of interactions. 
  • The Administrative Dashboard provides a common dataset for strategic discussions between deans' offices and faculty.
  • The COVID Dashboard was used during the pandemic to provide metrics to University leadership, who used that information to make policy decisions.
  • Research Administration metrics help to evaluate process efficiency and support organizational planning.

What are some of the challenges for DMA?

The ongoing migration of enterprise systems to various cloud vendor platforms requires flexibility in both the approach and tools used to develop data flows to the data warehouse. For instance, some vendors require proprietary tools to access data, curtail the amount of data that can be extracted at one time, impose charges on data flows, or pre-define the elements in data sets. The challenge is developing data flows that meet requirements efficiently and economically, as well as planning for the technical skills the team will need to develop and support data flows moving forward.

The sequencing of cloud migrations is also challenging. Planning to transition the current BI Platform to a cloud platform is proposed to begin in FY27 after several other enterprise cloud migrations are completed. Re-development will be required for all existing data warehouse integrations to complete that transition to the cloud.

Data security continues to be a challenge. Significant data breaches have been reported recently at other institutions; we don’t want to join that list!

DMA works closely with the Information Security Office and other Northwestern IT teams to regularly apply vendor security patches, evaluate and close security risks based on current market threats, and ensure that authentication standards are in place to validate that those accessing data are authorized.

Demand for new development exceeds the capacity of work that the team can support. This is an ongoing challenge. We work with business leaders and other IT teams across campus to prioritize requests and develop an annual portfolio of work representing the highest-value projects to the overall University. We then re-evaluate that portfolio against new requests quarterly, ensuring that DMA development aligns with business priorities. Unfortunately, there are some requests that would bring value to schools and units that we can’t act upon.

What emerging technology do you think will have the biggest impact on data analytics?

Artificial intelligence/machine learning-driven interfaces will continue to make data analysis more accessible to consumers without technical training. This technology will ultimately allow decision makers to identify trends and risks proactively and get information that answers ad-hoc inquiries both independently and more quickly. Easier and quicker access to relevant information will encourage data-driven decision-making.

However, automated interfaces also come with risks. Data must be carefully curated, and extensive meta-data must be maintained to support automated analysis and ensure that results accurately reflect Northwestern business definitions. Many vendors are offering new products in this area, and we continue to monitor the marketplace to evaluate which options will best support Northwestern’s needs.

What is your favorite place on campus?

My favorite place on campus is the lakefront green space behind the Pick Staiger Concert Hall. When the weather is nice, there is always a group of students enjoying the space. The views of Lake Michigan and the Evanston campus are incredible, and the Chicago skyline is in the distance. It is the perfect destination for a campus walk or an outside lunch meetup.

Evanston campus on the lakefront