An Authoritative Source of the Truth Why you

An Authoritative Source of the Truth: Why you Need Data Governance Tim Coley, Ph. D. Principal Strategic Consultant Ellucian

Disclaimer Statements about Ellucian products and services are confidential and proprietary to Ellucian. This presentation is not a commitment, promise or other obligation to deliver any material code or functionality, and it should not be relied upon in making any purchase decision. Development and release of Ellucian products and services may change, without prior notice, at Ellucian’s discretion. © 2018 Ellucian 2

Session rules of etiquette • We have time for questions at the end, but feel free to ask questions as we go • Please share your experience and expertise Thank you for your cooperation! © 2018 Ellucian 3

Agenda 1 Introduction 2 Data Governance Definitions 3 Data Governance Components 4 Data Governance Principles 5 Some Data Governance Issues to Think About 6 Closing © 2018 Ellucian 4

Introduction © 2017 Ellucian 5

About Me… Henry De. Vries • Management Consultant, Principal Targeted services for Business Analytics • Ph. D. Cornell University 43+ years in higher education • Faculty member, administrator, researcher • 16 years as CIO at Calvin College in Grand Rapids, MI • 13 years (concurrently) as CFO • Active in NACUBO, CACUBO, EDUCAUSE © 2018 Ellucian 6

Introduction We will explore the various components of a data governance program We will explore some of the common issues that create challenges to a data governance program We will explore some ways to align your business analytics / reporting infrastructure into a framework that supports data governance © 2018 Ellucian 7

Data Governance Definitions © 2017 Ellucian 8

What is it? Data Governance is high-level planning and control over data management. The exercise of authority, control and shared decision-making (planning, monitoring and enforcement) over the management of data assets. DAMA (Data Management Association) www. dama. org © 2018 Ellucian 9

Where does it Apply? Data governance processes apply to all of the components of the business analytics infrastructure – people, processes, policies, organizational development tools, and technology. Data Governance is a component of institutional governance. © 2018 Ellucian 10

Why? The objectives of data governance are to: • Enable better decision-making • Reduce operational friction • Protect the needs of data stakeholders • Assure data accuracy and quality • Train management and staff to adopt common approaches to data issues • Reduce costs and increase effectiveness through coordination of efforts • Ensure transparency of processes © 2018 Ellucian 11

The Need for Data Governance Institutions are increasingly enthusiastic about data-informed decision making and institutional performance management • You need quality data to analyze and manage institutional outcomes So, back to the Guiding Principle • An authoritative source of the truth (data) Data Governance is designed to help the institution assure that desired level of data quality. © 2018 Ellucian 12

Some Symptoms that you need Data Governance “Your” numbers don’t match “my” numbers • …. so I’ll create my own database Multiple data sources for the same type of data • How many shadow databases exist at your institution? • What impacts does this have? Data validation issues • Do you know who is responsible for validation, what will be validated, when should data be validated, and how is it done? Transparency • You spend more time auditing the reports for “correctness” of the data than using the report. © 2018 Ellucian 13

Data Governance Components © 2017 Ellucian 14

Component #1 – Data Ownership An institution needs an infrastructure to establish who “owns” the data at an institution. That’s not as simple as it seems. It is also important to distinguish the other data roles, such as data governance council, data trustee, data steward, data custodian and data consumer (end-user). © 2018 Ellucian 15

Component #2 – Data Quality An institution needs an infrastructure to govern how data elements are defined, recorded, and displayed, i. e. , a data dictionary. Data standards are also important to ensure that all data are defined consistently, input accurately, errors are corrected, and that data correctness and completeness are maintained. © 2018 Ellucian 16

Component #3 – Data Access An institution needs an infrastructure to govern how data are classified (public, sensitive, restricted) and who receives access to what. This also intersects with external compliance requirements, such as FERPA, HIPAA, PCI-DSS, FIPPA, etc. © 2018 Ellucian 17

Component #4 – Data Security An institution needs an infrastructure to govern how and where data are stored, handled, shared, distributed and protected. This requires a comprehensive set of policies and procedures for both personnel and IT resources. There is often intersection with external compliance directives, e. g. , PCI-DSS, HIPAA, GDPR, etc. © 2018 Ellucian 18

Data Governance Principles © 2017 Ellucian 19

Business Analytics Strategy Services Improve Information for Decision Making Information Determine Key Performance Measures Performance Metrics Workshop Balanced Scorecard Strategy Map Information to Measure and Monitor Improve Data Quality Data Governance Service Guidance for Data Governance Mechanism to Govern Institutional Data Ensure Infrastructure Readiness Reporting Review Service Understand Current State Future State Roadmap Sound Infrastructure to Build Upon Infrastructure (people, process, policies, OD tools, technology) Client Need Ellucian Offer Ellucian Delivers Client Outcome © 2018 Ellucian 20

Data Governance Service Data Governance is high-level planning and control over data management. If you cannot trust the data, then turning data into useful information for reporting results, running analysis, decision making and developing strategies is difficult to impossible. The Data Governance Service provides clients with the necessary tools and support to create a solid data governance roadmap and the ongoing support to move forward that plan. Built on 4 Guiding Principles (Best Practices) © 2018 Ellucian 21

#1 - The Infrastructure Model People Policies Processes Technology OD Tools © 2018 Ellucian 22

Infrastructure Deals With -People Organizational Development Tools • Leadership • Staff skills • Skill distribution • • • Policies • • • Acceptable Use Policies for Technology Password policy Data access Data classification Information security Processes • • • Data handling Data backup/recovery Business process modeling Internal and external reporting Compliance reporting Change management Project management Communications strategy Knowledge transfer Human capital management Organizational development Technology • • Customizations and localizations to the baseline ERP Authorized external data sources Data repositories Data warehousing systems Reporting software Statistical analysis software Visualization software © 2018 Ellucian 23

#2 - Authoritative Source for the Data All reports for a given information domain should derive from a single agreed-upon authoritative data source (“single source of the truth”) that is universally endorsed as correct and trustworthy, the system of record. Corollary #1 – When similar data are stored in more than 1 location, one must be the authoritative source for all others. Corollary #2 – Shadow databases and departmental data marts should either be eliminated or have the relevant data incorporated into institutionally sanctioned data repositories. © 2018 Ellucian 24

#3 - Standardization Data Governance requires standardization of enterprise data. Data standards are a key foundation for implementing the data quality component of data governance. The goal of a data standard is to enable the sharing or exchange of information between multiple parties in a way that guarantees that the interacting parties share the same understanding of what is represented within that information. Desired Outcome: To ensure consistent understanding of key data element and data value across various functional offices that use this data in common. © 2018 Ellucian 25

#4 – Leverage the Operational Efficiency of your ERP The ERP should serve as the system of record for all business transactions and all business information. The ERP and its directly affiliated data warehousing tools should serve as the sole source system for institutional operational (transactional) reporting. The ERP system is designed for the majority of activity to be carried out by the enduser, with significant automation of standard tasks and minimal intermediation by the IT support organization. End users need to fully understand: • Their ERP (direct access and “self-service”) • The specific data elements, and their meaning, within their functional area • How reporting connects to their ERP data © 2018 Ellucian 26

Some Common Issues to Think About © 2017 Ellucian 27

Data Ownership Who owns my record? Clear, well-understood roles are critical to resolve conflicts and challenges • Data Governance Council • Data Trustees / Owners • Date Stewards • Data Custodians • Data Creators • Data Consumers: internal and external This is a governance question, not an IT one. • Executive Sponsorship © 2018 Ellucian 28

Data Quality Procedures • Validation during data entry • • e. g. , address-checking, duplicate records Error correction procedures Policies • Data dictionary: identifies standard elements for data use for key business terms • Meaning (definition) of the data element • Validation, format, display • Metadata © 2018 Ellucian 29

Shadow Databases Often the most significant problem for overall institutional data quality • Lack of synchronization with master database • Additional data not in the master database • Invisible data (not shared) a/k/a “hidden data” • Security, backup / recovery • Inconsistent reporting • “arguing more about the data, than the question at hand” © 2018 Ellucian 30

Customizations, Localizations Customizations – changes to the baseline that have been made to reflect local preferences. Localizations – changes to the baseline that are necessary to do business in your specific environment. Are they moving from the transactional database into the business analytics stack (“ODS/EDW” or data repository or the data lake)? © 2018 Ellucian 31

External Data Sources Bolt-ons, Add-ons, Saa. S • e. g. , recruiting/admissions tools, CRM systems • Incomplete or asymmetrical data transfer to/from the transactional database • Subsequent difficulty in reporting performance metrics © 2018 Ellucian 32

Data Access Community Definitions (AUP) • Public Data • Sensitive Data • • Community Information • Private Information • Confidential Information Restricted Data External Factors • FERPA, HIPAA, GDPR, FIPPA, PCI-DSS, PHI, etc. © 2018 Ellucian 33

Data Access - Reporting As business analytics initiatives open up the data to a broader base of data consumers across the campus, how do you control “who can see what? ” Institutional governance question – Is this statement true for your institution? • “As a general principle of access, XXX University data (regardless of who collects or maintains it) will be shared among those employees whose work can be done more effectively by knowledge of such information. ” © 2018 Ellucian 34

Data Security People-based… • Knowledge transfer about how to handle sensitive/restricted data • Policies – FERPA, GLBA, GDPR • Procedures – can you say “USB memory stick”? Technology-based… • Data backup / restore • Data encryption • Data transfer • Audit trail © 2018 Ellucian 35

How do you Measure Progress? Education of • People Adoption of • Policies • Procedures • Tools Data Governance KPIs… • Number of data integrity open Issues • Number of Data Quality issues resolved • Number of defined data sources in the Data Dictionary © 2018 Ellucian 36

How Does Ellucian Provide Data Governance Services? Three stage engagement • • On-Site • Information Gathering focus groups with IT, IR and functional offices • One-day training workshop to get started with each of the four components Follow-up • Written Reporting of Findings and Recommendations including a roadmap • Ongoing Advisory services © 2018 Ellucian 37

Closing © 2017 Ellucian 38

Summary Data Governance is a key component in the establishment of a reliable infrastructure to support data-informed decision-making Data Governance has four primary components: ownership, quality, access, and security Data Governance is far-reaching across the institution and is bigger than just IT, it is an important part of institutional governance. Thus, it is must be a campus-wide effort. © 2018 Ellucian 39

Follow-up Are you interested in learning more about Ellucian’s Data Governance Service? • Catch me after this talk or stop by the Ellucian booth in the exhibit hall • Send me an e-mail: tim. coley@ellucian. com Would you like to win a free hour of data governance consulting? • Drop your business card off at the Ellucian booth in the exhibit hall for a drawing Ellucian will be e-mailing a copy of this presentation to you after the conference. © 2018 Ellucian 40

Questions & Answers © 2017 Ellucian 41

Thank you. TIM COLEY, PH. D. tim. coley@ellucian. com