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Case Study: Cornell University

Cornell is a privately endowed research university and a partner of the State University of New York. WhereScape talked with Data Warehousing Manager Jeff Christen and Data Warehouse Developer Chris Grippin about the University’s conversion from IBM Cognos Data Manager to WhereScape RED. WhereScape RED is providing Cornell automated data integration for its Oracle data warehouses that manage crucial student, constituent and financial data.

We have been very pleased with the automated data integration capabilities and intuitive nature that WhereScape RED provides. We plan to move our entire core data mart processes over to WhereScape RED over the next calendar year

Jeff Christen, Data Warehousing Manager Cornell University

What does your data warehouse environment and staffing look like?

Cornell has an Oracle 11.2 data warehouse, with plans to move to Oracle 12 later in the year. The warehouse environment is made up of three major subject areas—the student data mart, which is accessed university-wide by a potential community of 20,000 users and contains 300 presentation tables which are refreshed daily; a constituent database, which drives a lot of the marketing activities as we reach out to donors and other benefactors; and the university’s financial data mart.We have four data warehouse developers, with individuals responsible for each of the data warehouse subject areas.

What prompted the search for a new enterprise data integration tool?

We previously used IBM Cognos Data Manager to transform and merge data into our Oracle data warehouse, but support for the product will be discontinued later this year prompting the search for a new solution.

In doing your due diligence, what did you look for in a new solution?

In order to replace Data Manager, we knew we needed to find a tool to format the data into dimensional models and perform the data transformations. We looked for an open metadata-based solution so in the future we could do data lineage-type extractions for analytics and reporting. Most of the solutions we evaluated had a closed model, and some were even too bizarre to navigate. In addition, many of the tools we evaluated were sold with CPU-based pricing, which was cost prohibitive for us. We were very attracted to developer-based pricing. In addition, we felt a proof of concept with our own data set was crucial to the decision-making process. For our proof-of-concept, Chris, with support from WhereScape, was able to convert one of the core data model load processes in our financial data mart from Data Manager to WhereScape RED.

After your extensive due diligence, you chose WhereScape RED. Why?

WhereScape was a leader in all areas. The metadata tables that WhereScape RED utilizes are truly open and easily accessible as the software is very intuitive. The developer-based licensing model is also far more attractive for WhereScape RED. The financial data warehouse we are currently converting runs on two 24 core CPU database servers. If we licensed by core, it would have been cost-prohibitive for us. We don’t have the 48 CPU cores for ETL performance; it is for query performance downstream, for the users, as well as creating a fail-safe environment. Most of the vendors we evaluated tried to license us for 48 cores—and that is just one of our data warehouses. We were able to purchase a four-person WhereScape RED developer license which is proving very cost-effective for us. We are not going to be “nickled and dimed” as our environment configurations change or as our data volumes grow—both of which are inevitable for us.

We give WhereScape RED high marks. We understand the automated PL/SQL WhereScape RED is generating. We have visibility into generated updates or custom procedures via the metadata layer. WhereScape RED is highly complementary to our Oracle environment.

Cornell University

What are your successes with WhereScape to date?

We started our conversion from Data Manager to WhereScape RED early this year. We are nearing the successful completion of our financial data warehouse conversion using WhereScape RED. The largest table we converted was 5.5 million rows. We are polishing and fine-tuning our conversion processes before we undertake the conversion of the other subject areas which will happen this year. Using WhereScape RED we quickly developed and deployed a new subject area for tracking employee position history from WorkDay. We have also been using RED to develop our new research administration data mart. We have been very pleased with the automated data integration capabilities and intuitive nature that WhereScape RED provides. We plan to move our entire core data mart processes over to WhereScape RED over the next calendar year.