Data Management Program Overview 5/12/2018 Data Management Program Overview February 6, 2017

Agenda Recap of 12/18 discussion: Key Takeaways and Next Steps CIO Outreach – what we have heard so far Implementation Strategy and Plan

Recap of 12/18 Discussion

Recap of 12/18 Discussion Takeaways from our last discussion: Improve understanding of the pain points in the schools There is acknowledged value in simplifying the Data API Architecture Avoid the perception of “boiling the ocean”, articulate incremental approaches How will this improve our existing administrative data? How will this enable strategic programs (SIS, IAM) and other major future initiatives?

Recap of 12/18 Discussion Next steps: Convene a small group in January to focus on: pain points, opportunities Establish an Executive Committee and otherwise improve representation from/collaboration with schools and departments Better define the strategy Simple, clear definition of the strategy How will this strategy be implemented, and what are the specific benefits to the schools?

CIO Outreach: What we have heard so far

What we have heard so far Reporting Tools & Access to Data Models HLS uses Business Objects, would consider OBI/Qlikview HMS, GSE, GSAS have made or are considering investments in Tableau Access to consistent local and central/administrative data is a priority (HLS, HKS, HMS) HLS would like to have better access to central administrative data generally Accurate, well-defined Administrative Data HMS would like to better understand Faculty data and where it is sourced from to better manage data quality. HDS and HKS expressed that many of the schools use the same data differently, and this impacts efficiency and productivity. Simplified Data Exchange Architecture HLS and HBS may be able to use existing Student APIs, but it is not clear what data is available and if it meets the needs. Discussions are ongoing. HMS pulls back data into it’s data warehouse that takes hours to run each day All so far have acknowledged how time consuming and expensive it is to connect our systems

Implementation Strategy and Plan

Review: Vision and Strategic Objectives Program Vision To harness the significant value of Harvard’s data assets: We strive to reduce costs and enable improved decision-making for our staff, faculty, and students through the effective use of data management services. Strategic Objectives Provide people with better reporting tools and access to data models Deliver accurate, well-defined administrative data that are easy to find and understand Simplify the way we exchange data between our systems Program Strategy Invest in a “Data Management Infrastructure” to improve the value of future investments Fully implement tools from we already own Apply tools to existing priority backlog (SIS, IAM, Finance) for quick wins Partner with new projects to deliver end-to-end ROI Continued engagement with schools and central units to identify pain points and solutions

Strategic Objective 1 – Implementation Strategy and Plan Provide people with better tools and access to the data they need to do their jobs Make the BI tools we have today (OBI, Qlikview) available to everyone Make the data we have today more readily available Train staff to use BI tools and data models Implementation Plan Stand up university BI tool platform service Select one school and conduct OBI/Qlik pilot Develop provisioning process for administrative data models Select one administrative data model and provide new access to select users Pilot with one school to make its local data sources available in OBI/Qlik Develop BI training program for business power users and IT Staff Pilot BI training for business power users Pilot BI training for IT staff

Strategic Objective 2 – Implementation Strategy and Plan Deliver accurate, well-defined administrative data that are easy to find and understand Implement a common, shared data glossary Implement streamlined data access provisioning Document the data that we have today Work with initiatives during their projects to document new data Implementation Plan Stand up a university data glossary service Implement a tool and service to streamline the provisioning of access to our data Document our existing administrative data assets Pilots with 1-2 administrative data teams (Stu, Res. Admin, HR, Fin, Alumni, IAM) to implement existing data documentation into the business glossary Pilot with one school to implement a targeted local data source into the business glossary Develop and implement standards on data documentation for new initiatives Engage with Position Management, Buy-to-Pay, Contingent Workforce, and others Establish a data glossary “Community of Practice” with users across the university

Strategic Objective 3 – Implementation Strategy and Plan Simplify the way we exchange data between our systems Implement a common, shared data API platform Make API’s that we already have today available to everyone Work with initiatives during their projects to use this platform Retire current point-to-point solutions over time Train IT staff on how to use this API platform Implementation Plan Stand up a university API platform service Build new APIs and register existing APIs Pilot one new “enterprise” data service (ie. Person) and incrementally build API solution Partner with schools on a pilot to build APIs on this new platform Register existing APIs (ie. Student, HR, Finance) in the API Gateway Develop and implement EA standards on APIs for new initiatives Engage with Position Management, Buy-to-Pay, Contingent Workforce, and others Catalog legacy point-to-point solutions and prioritize for conversion to new platform Convert 2-3 central and 2-3 school point-to-point solutions Develop and implement API development training program for IT staff in schools and center

Next Steps Collibra Data Glossary and Mulesoft/API “Working Groups” are being formed CIO outreach is ongoing, further engagement? Second “Small Group” meeting planned for next week Early discussions on Gartner Roundtable to be hosted at Harvard Outreach to other institutions is ongoing Presentation to ITCRB on 2/22

Appendix

Business Benefits and High Level Timeline

Data Management High Level Business Benefits Today Data Management Tomorrow Data is hard to find and access Too many tools that cost too much Limited access to existing data models People don’t have data they need Data is difficult to understand What does this data mean? Where did it come from? Is it the right data for my needs? Data is expensive to exchange One-off point-to-point solutions Duplicated effort to rebuild integrations Too much time and money spent Reporting tools and data models On-demand, self service reporting tools Access to administrative data models Improved end-user skills, competencies Data asset library Intuitive business data glossary Report catalogs, data dictionaries Well-defined, discoverable data assets Data exchange architecture Data exchange and integration framework Reusable data exchange services Reduced cost and faster delivery