Data Sources

AM360 Data Sources

The DSI team has built a variety of data sources to support the AM360 dashboards with a focus on accuracy, timeliness and utility. The data is sourced from application data and transformed into the information needed to support the business questions addressed in each of the dashboards. While the data sources were built to address the specific needs of AM360 dashboards, they have been expanded when appropriate to include additional data that may be useful in other future projects.

How does the data flow through DSI systems?


If you are interested in learning more about DSI's architecture and how the data flows through our systems, read about here

How often is the data updated?

The Student Systems and Financial data are updated on a nightly basis using day old application data. Human Resource data are updated on a monthly basis on the 27th of each month. All of our update processes clear and rebuild current and historical data each time, so they are always ‘current state’ as opposed to being snapshots representing specific points in time.

Based on reporting requirements the amount of history may vary from one application to the next, but in general we display the most recently recorded data plus 4 prior years, but the data captured currently goes back to 2011. In the future we expect to extend the number of years of historical data we save to support predictive analytics and our Denodo Self Service application which allows users to select and download data directly.

How is this data validated?

While building these data sources we employ multiple levels of quality assurance to insure that we are providing information to decision makers that is accurate, timely and consistent. First we compare our tables to source system tables, then insure that the data is transformed properly as it moves through the system, and finally when possible we compare to the IUIE, UIRR reports and other existing sources as appropriate.

What metadata is available?

Data Cookbook is the tool we use for capturing and storing metadata related to our Tableau dashboards and Denodo interface views. We also capture metadata called definitions that describe the individual columns, or fields, in the data sources we have built. This metadata includes the business purpose, sample values, classification attributes, technical description and logic used to populate the column. Functional area experts are involved in writing the definitions, and data managers approve the content prior to release.

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