breaking silos and building a university data community - sponsored by skillsurvey (263245761)

8/9/2019 Breaking Silos and Building a University Data Community - Sponsored by SkillSurvey (263245761)

http://slidepdf.com/reader/full/breaking-silos-and-building-a-university-data-community-sponsored-by-skillsurvey 1/54

Breaking Silos And Building a University

Data Community

Craig Rudick Malar Perumalraja Associate Director of IR Database Administrator

University of Kentucky Lynn University

[email protected] [email protected]

This presentation leaves copyright of the content to the presenter. Unless otherwise noted in the materials, uploaded content

carries the Creative Commons Attribution-NonCommercial-ShareAlike license, which grants usage to the general public

with the stipulated criteria.

EDUCAUSE CONNECT San Antonio 2015

mailto:[email protected]


https://creativecommons.org/licenses/by-nc-sa/3.0/

https://creativecommons.org/licenses/by-nc-sa/3.0/





Why is Data Important?

Because SCIENCE!• It’s how we know stuff

If we drop two students froma tower, which onegraduates first?




Image source:www.dishful-thinki

ng.comReference: https://www.ted.com/talks/kenneth_cukier_big_data_is_better_data



http://www.dishful-thinking.com/criss-cross-apple-pie/





source: http://activerain.trulia.com/blogsview/4509000/pumpkinfest-october-13--2014






MORE DATAMORE

ACCURATEANALYSES

MORE CONFIDENTDECISIONMAKING

BETTER

DECISION MEANS* Student Success

* Greater Operational

Efficiency

* Reduced Risk




Q & A

How is lack of access to data hamperingdecision-making on your campus?

• Is there a single piece of data you most wishyou had?

• Are institutional siloes preventing data access?

How do you empower people to make betterdata-informed decisions?

• Do you have the tools and skills required tounderstand and analyze data?




Challenges

source: http://www.making-sense.org/page.php?page=1




Lynn University Challenge = DataChaos!!!

Organizational Silos

Lack of Communication and Cooperation

Multiple and Incompatible Data Systems Conflicting Processes

Conflicting Definitions

Conflicting Numbers

Duplication of Efforts

Source: http://www.ektron.com/Blogs/Chris-Denaro/Why-Silos-Are-Bad-In-Higher-Education/




Organizational ChartIT Department

Office ofCIO

InformationSystems

CardSystems

Networkand Telecom

SupportServices

InstitutionalResearch

Library




IT Challenges

Lack of Coordination among IT Units

Growth in systems and services (Service

Catalog) Audits

Informal Governance




Data Challenges

Consistency and Reproducibility

• IR vs. BI + siloed systems

• Poor data archival

• Never the Same Business Rule Twice

I need data. Who do I ask?




Analysis Capabilities

Data is not information





The Underpants Gnomes Theory of Big Data





The Underpants Gnomes Theory of Big Data

Underpants=

Data




Group Activity #1: Voting

Identify and explore thechallenges at your Institution1. Each table divides into pairs

2. Vote for similar challenges

3. Write any other challenges on a sticky noteand place it under “other” column on theposter board.

4. Discussion




Source: http://www.bluleadz.com/blog/the-top-5-email-marketing-challenges-and-how-to-overcome-them




Lynn UniversityIT Governance

IT UNITCommittee

Office of theCIO

Networking

Telecom

HelpdeskLibrary

InformationSystems

Card Office




IT Governance

Project Management

Hurricane Plan

Identity and AccessManagement

Change Management




Change Management

Implemented a process

Established a workflow

Set overall Goal

Controls + Communication + Collaboration =

Coordination




Change Management Workflow withTimelines

Submits RFC to

CMT by noonon Monday

The RFC sent torequestorsDirector for

Approval

Director

Approved?

CMT

ReviewsRFC

ChangeImplemented

YES

NO

CMT

Approved?

NO

YES

Requesterwill benotified

If denied sent back to

requester

If denied sent back to

requester CIOOverride

? NO

YES

Prior to Mondayat Noon

Tuesday




CMT Video




CM: Lessons Learned

Lots of work and dedication

Creating and Implementing the process involvedcosts

- 6 months for 8 FTEs, meeting 2-3 hours a week

- Primary for CMT 7 hours a week in preparation of requests

- CMT 2 hours a week to review and approve requests

Purpose – Reporting or Informational

Start small Change is Hard




Data Governance

source: http://www.kid.co.za/kid_mdm-serv-gov.htmlEDUCAUSE CONNECT San Antonio 2015



Source: https://www.pinterest.com/pin/310607705519762660/




Data Governance Committee

The Mission – To Establish and oversee the

university’s Data Governance process.

Composition – This committee is advisory tothe university cabinet. The Director of IRPAwill serve as chair of the Data GovernanceCommittee. Membership of the committee will

consist of the primary data stewards of allacademic and non-academic universitydivisions engaged in collection, validation, andreporting of data.




Data Governance Committee Charge

System and Process Documentation

Data Quality and Integrity

Training, Communication, Decision Supportand Outreach




Goals

Primary:

Identify & Document Data related processes

Identify Major Data Elements Define Major Data Elements

Secondary:

Identify Systems of Record

Identify & Assign Data Owners




Accomplishments !!

Identify the Need for Process Improvement• Redundancy or gaps in process

• Communication between departments

Identify Opportunities for Possible ProcessAutomation• Data bridges or imports between systems

Identify Possible Improvements in UniversityReporting Processes• How, who, what and from where?




Accomplishments in 1 year !!

Identified around 19 functional units

Identified & documented 56 processes

Identified 71 Microsoft Access databases

Identified 42 possible recommendations




DG New Challenges

Maintain subcommittee momentum,commitment & documentation integrity

Creating awareness, while gainingexcitement about data governance

Limited IT resources




Priority Matrix

High Medium

Medium Low

3 or more

Functional units

1 or 2

Functional units

CriticalBusiness process

Non Critical

Business process




Next Steps

InformationTechnology

DataGovernance

ChangeManagement




IT DGC

CM

Next Steps




Building A Data Community

Merger of IR and BI

Total Data Integration Strategy

Community of Practice Maximize Analysis Capabilities




Building A Data Community




IR + BI = AA

UK Analytics andTechnologies

IR and BI merged into

Advanced Analytics (AA)

AA does all regulatoryand operational reporting

Data Science (DS) group

established within AA todo analysis

Data Science is core ofthe new IR

BI IR

AA

AA(DS)

AA IR(DS)




One Data Warehouse toRule them All

SAP HANA as Data Warehouse

• In-Memory RDBMS

Data Models as final products

• Regulatory and Operational reporting

• Designed for Analysis

Integrate as much data as possible




And in the DarknessBind Them

Available

Enrollment

Retention

Majors, minors

Degrees

Courses/grades

Applicants

Demographics

Student Financials

Peer Tutoring

Instructors Faculty stats

Building utilization

In-Progress

Housing

Greek

Holds

Alerts

Advisors

Time-to-degree

Test scores

Micro-surveys

Transfer stats

HR details

Next Up

Surveys

Teacher/courseevaluations

Degree audit

High Schools

LMS

Campus recreation

Faculty research andsponsored projects




Analysts across University have direct access tounderlying data

• Start with a core group of early adopters

• “Crowd-Source” basic reporting At least one Super User in every College or unit

• Data access and analysis with Tableau

• Point-and-click interface

• Bi-weekly training seminars regularly attended by 30+

Community of Practice




Built by COP

Student Demographics Recruiting Map




Built by COP

Section Fill Rates Class Grade Distributions




IR Certified

IR designs “official”dashboards withcommon standards

• COP feedback anditerations

• COP has access tounderlying data and

definitions




Data definitions are multiple, iterative andconsensus-driven

• IR acts as unbiased arbiter

• Data Stewards are identified, but no formal group Units are finding us to ask to have their data put

into HANA

• “You can see mine if I can see yours”

When data becomes important, so does dataquality

• Missing instructors have fallen from ~20% to ~3%

Data Governance?




Group Activity #2

How Can You Get Your OrganizationProgress Along the Data Governance

Maturity Curve?

What Is Data Governance?

Why Is Data Governance Necessary?

Who should Be Involved, and How?




Reference: www.virtusa.com




Craig - Group Activity #3

1. Make a dashboard using your assigned datasource






2. Give your dashboard to the table next toyou

• Make a new dashboard using your original datasource plus this one






2. Give your dashboard to the table next toyou

• Make a new dashboard using your original datasource plus this one

3. Rotate again

• Make a dashboard using any data you canimagine!





1. Did you get new ideas from the othertables?

2. Did you agree on definitions? Multipledefinitions?

3. Did you use any statistics?

4. What do your data tables need to look like?

5. How will this help you make betterdecisions?




Final Discussion




Your Input is important to us!

Please remember to complete an evaluation of your session

using the mobile app.

SESSION EVALUATIONS

Source: http://www.knysnakeep.org/200000-fighting-words-for-knysna/thank-you-keyboard/

breaking silos and building a university data community - sponsored by skillsurvey (263245761)

Documents