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Building the Foundation for a Data-Driven Future

WWT and Washington University in St. Louis partner to build a public cloud-based enterprise data store that will support the University's data maturity goals well into the future.

February 17, 2020 4 minute read

Washington University in St. Louis (WashU) partnered with WWT to design and implement a public cloud-based enterprise data store — a foundational pillar of a mature data infrastructure. The multi-year engagement is part of WashU’s transformational program, MyDay, which aims to develop new ways to use and manage the data needed to run the University. A key first step in this process involves improving the University’s data maturity (i.e., their ability to collect, report and analyze data).

“Currently, our data is siloed and disjointed. While much of it lives in the same place — a data warehouse — it cannot be combined easily,” says Rooji Sugathan, Executive Director of Data Management. "If we want to analyze data from more than one area of the University, we have to pull that data separately, then combine it in another program such as Excel. For example, we may want to evaluate HR data and physical space data to compare how different units use our facilities. We cannot do that easily today.”

Understanding the current landscape

WWT began work in early 2019 by understanding WashU’s data and reporting landscape. As with many of our customers, WashU’s data comes from a mix of applications hosted either on-premises or in the cloud via software-as-a-service sources, soon to include Workday. WWT assessed the various options to extract data from each of the University's unique source systems.

Once we understood the back-end sources, we evaluated the front-end reporting needs. Different communities at WashU favored different business intelligence tools, and not all tools were directly connected to the existing data warehouse. WWT worked with WashU to determine which tools would need integrations to the new enterprise data store.

After gathering business and IT requirements, WWT began a period of iterative design and testing to develop an architecture for the enterprise data store. We developed proofs of concept for promising combinations of components, evaluating different ETL (extract, transform and load) tools, data lakes and data warehouse options in the process.

WWT regularly publishes similar labs and demos for both customers and the public to explore on wwt.com. For example, we recently released a demo on how to integrate data using Azure Data Factory

One of WWT's key differentiators is our ability to leverage our Advanced Technology Center (ATC) — a collection of physical and virtualized labs — to test integrations from traditional on-premises sources to public cloud platforms.

A platform for growth

Based on ATC testing results and our expert recommendations, WashU selected Microsoft Azure as the platform for its enterprise data store. Switching from on-premises servers to the cloud-based Azure will allow WashU to quickly scale its compute and storage resources as its needs change over time.

As WashU grows its data science analytics capabilities, it will also be able to utilize Azure’s Machine Learning Studio to develop and share predictive models. “The more we’re able to connect our data across different areas of the University, such as research, physical space and finance, the more robust our analytics capabilities will be in the future,” explained Sugathan.

WWT is currently helping WashU implement the enterprise data store, developing the foundational components in Azure as well as integrating data from the University's prioritized source systems.

Ensuring success from the beginning

Over the years, WWT has found that the adoption rate of public cloud services can sometimes falter without the right resources, creating overlooked staffing and skills gap issues. Therefore, as part of the engagement, WWT has committed to ensuring WashU’s IT resources are trained on the new cloud tools and data integration methods

Our ultimate goal is to accelerate WashU's data maturity journey by empowering the University to internally sustain and further mature this strategic capability on its own in the long run.

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