CSG Spring 2014 – Analytics Discussion

ECAR Analytics Maturity Index – could use it to assess which group to partner with to judge feasibility. 

NYU started analytics several years ago and chose certain kinds of data. 

Dave Vernon – Cornell
Hopes and dreams for the Cornell Office of Data Architecture and Analytics (ODAA)
Curent state fof data usability at Cornell: like a library system with hundreds of libraries, each with unique catalog systems (if any), each requiring esoteric knowledge, each dependent on specialists who don’t talk to each other.

Traditional “BI” -not analytics but report generation. Aging data governance.

ODAA – to support Cornell’s mission by maximizing the value of data resources. Act as a catalyst/focal point to enable access to teaching, research, and admin data. Acknowledge limited resource, but will attempt to maximize value of existing resources.

Rethink governance: success as the norm, restrictions only as needed? Broad campus involvement in data management – “freeing” of structured / unstructured data. Stop arguing over tools: OBIEE vs Tableau, etc. Form user groups – get the analysts talking. 

Service Strategy: Expand Institutional Intelligence initiative: create focused value from a select corpus of admin data (metadata, data provenance, governance, and sustainable funding). Cost recovered reporting and analytics services. User groups, consultants, catalog and promulgate admin and research data resources. 

Resource strategy: What do you put together in this office? Oracle people, reporting people. Re-aloacate savings. Add skilled data and analytics professionals. Modest investment in legacy tool refresh. People are getting stuck in that discussions of tools.

Measures of Success: ODAA becomes a known and trusted resource. Cultural evolution – open not insular. Data becomes actionable, self-service. Broad campus involvement data management, “freeing” of data – have to work on data stewards to convince them that they have to make a compelling argument to keep data private. Continued success of legacy services.

At NYU IR owns the data stewardship and governance, but there is a group in a functional unit (not IT) that acts as the front door for data access. Currently just admin data focus, but growing out of that. Two recent challenges – student access to data (pressing governance structure), and learning analytics (people want access to LMS click streams – what about privacy concerns?).

Stanford – IR group reports to provost (like 15 people) do admin data. Group reports to dean of research for research data. Teaching & learning under another VP. Groups specialize, reducing conflict. Data scientists are part of those groups. 

Washington spinning up data science studio with research people, IT, library people as a physical space for people to collocate. 

Jim Phelps – can we use the opportunity of replacing ERPs to have the larger discussion about data access and analytics?

Notre Dame halted BI effort to go deeply into a data governance process, and as part of that are getting a handle on all of the sets of data they have. Building a data portal that catalogs reports. More a collection of data definitions rather than a catalog of data. data.nd.edu A concept at this point, but moving in that direction. Registry of data – all data must be addressable by url. Catalog shows existing reports, showing shat roles are necessary to get access. Terms used in the data are defined. 

Duke – Not hearing demand for this on campus, but getting good information on IT activity using Splunk on data streams. Could get traction by showing competencies in analysis.

At NYU had a new VP for Enrollment Management who had lots of data analysis expertise, who wowed the Board with sophisticated analyses, driving demand for that in other applications. 

Data Science Venn diagram – http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

Dave Vernon – There’s an opportunity to ride the big data wave to add value by bringing people together and getting the conversations going and make people feel included. 

How are these teams staffed? Can’t expect to hire someone who knows all the pieces, so you have to have cross-functional teams to bring skills together. Michigan State has a Master’s program in analytics, so bringing some good people in there. Last four hires at Notre Dame have been right off the campus. Now have 8 FTE in BI space. 

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