Live, Historical Snapshot, Or Yesterday’s ODS Data?

Which Do I Choose?Kimm Sundal, Decision System Support Specialist - SDBOR

John Van Weeren, Principal – ASR Analytics, LLC

Agenda

•South Dakota Board of Regents Conversion Journey • Getting out of our comfort zone• Evolving to meet new demands for data

•Technically Speaking• What is a frozen extract and use in analysis? • What is an ODS and its uses?• Student Success Analytics – the next step!

A Journey Starts with a Single Step

Supporting Data Informed Decision Making

• Develop: • a culture of evidence and inquiry using data

• By Improving:• Integration, access, and accuracy of data

• Through the implementation of:• A comprehensive Decision Support System

• Using:• Established methodologies and best practices

Understanding the Stages of the BI Journey

Operational

Process

Strategic

Reporting Analyzing Predicting

Source: Adapted from: “Datatel - PESC 2008: Application of BI in Higher Education”

Which Data Structure Support Which Needs?

Operational

Process

Strategic

Real-time Daily (ODS), Per Term (SE) Daily

Student Success Analytics (DW)

Operational Data Store (ODS)

LIVE IBM Cognos Enterprise BI Platform

Student Extract

Data Latency:

Single Version of the Truth…OR is it?

•Colleague/Banner live data•Student Enrollment Extract•ODS – Operational Data Store•Student Success Analytics

Live Data

• Originally the only way to get data after system implementation• Primarily available to Finance, HR, and Admissions (and, of course, IT)

Benefits• Immediate needs for timely “as of now”• Supports data entry validation and business workflow accuracy• Can be used for reconciliation and data feeds

Live Data

Challenges• Performance impact on transactional processing• Managing security• Lack of reporting tools, not self service oriented • Data structure requires detailed familiarity with data, tech knowledge• Difficult to build, maintain, and keep consistency with derived/summary data• Very different experiences across systems

Mitigation• Move users to Extract/ODS unless real time data is absolute requirement

Frozen Student Extract

• Arose out of need to address needs not possible with live data• Original method used by SDBOR for point in time reporting

• Student Enrollment data frozen or extracted three times each semester• Beginning of Semester – Record type 1• Census Date – Record type 2• End of Term – Record type 3

Benefits• Consistency over time• Information in one place• Organized to meet the majority of the student reporting needs

Frozen Student Extract

Challenges• Only three time series capture points - inadequate for predicting/forecasting• Difficult to adapt data structure given implementation tools/method

• Couldn’t evolve for increasing demands, additional external systems• Business rule/calculation definitions not easy to “see” and understand as a user

• Tendency to export data and create new data sets, definitions, and diverge from original intent creating confusion if not the “official” reports

Mitigation• Develop a whole new approach and decision support architecture

ODS – Operational Data Store

• Banner ODS introduced to SDBOR environment - 2006• Colleague ODS introduced to SDBOR environment – 2014

Benefits• Data collection / organization is designed for reporting• Common definitions and business rules applied consistently• Significantly more data exposed than Student Extract• Paved way for Analytics with more data combined in one place• Provided a self-service model for enterprise reporting

ODS – Operational Data Store

Challenges• Does not have ALL the data from the live transactional systems• Relational data structure sill requires a fair bit of knowledge, tech skills• Data latency of last night perceived as a negative• New skills and responsibilities required of IT to monitor and support

Mitigation• Implement a process for rapid response evaluation to add data to ODS• Implement a modern BI platform with semantic layer to hide tech complexity• Semantic layer enforces appropriate join/query of data, consistent usage• Educate users – real time rarely necessary, ODS is newer than Extract

Student Success AnalyticsThe Next Step

Student Success Analytics – provides a data driven environment to allow the SDBOR to develop a fact-based management system to drive decisions, actions, and outcomes.

Benefits• Comprehensive longitudinal (time-series) data warehouse• Analytics and forecasting in a significantly more flexible way to look at data• Alignment of information needs with university strategic objectives• Striking a balance between SDBOR and university goals

Student Success AnalyticsThe Next Step

Challenges• Overcoming resistance to numbers not matching EXACTLY to older methods• Learning curve to understand data at various points in time (snapshots)• Data structure is so flexible it can be confusing, adding data to it is different

Mitigation• Numbers never match for lots of reasons – educate, define purpose • Find the users who “get it”, leverage and include them for testing, rollout• Find experts who understand BI, constantly train, use demos and iterate• Plan early to hire the right skills in IT, leverage consulting to transition

Decisions – Actions – Outcomes• Driven by functional business questions, business processes and

information needs• How are we doing? (dashboards & scorecards)• Why? (reporting & analytics)• What should we be doing? (planning & forecasting)

Plan

Execute

Measure

Analyze

Success – Our Definition• Efficient access to data• Consistency…consistency…consistency• Elimination of “shadow systems”• Collaboration and knowledge transfer within

the Regental system.• Broader thinking

Cognos – Consolidating Tools and Access• Prior legacy of many tools and methods

• Access, Oracle tools, spreadsheets, all technical

• Good semantic layer (Frameworks) essential • Enforces consistency, provides security• Dealing with multiple systems and sources• Easier to integrate data at semantic level

• Gives users one place to go and one tool to learn for data different structures / latency

• Takes time and training to shift

Thank you!Kimm Sundal, Decision System Support SpecialistSouth Dakota Board of RegentsJohn Van Weeren, Principal ASR Analytics, LLC

Supplemental Information

South Dakota Board of Regents• The South Dakota Board of Regents System (SDBOR) is comprised of

six four-year public universities, two special K-12 schools, three higher education centers, and the Executive Director’s Office. The SDBOR serves approximately 26,000 full-time student equivalents annually in credit-based courses and produces about 5,000 graduates a year. The system employs approximately 5,500 full-time equivalent employees annually. Excluding students, and including part-time employees, the number of staff approximates 6,754 any given month.

ASR Corporate Summary• Founded in 2004, ASR Analytics, LLC is a management

consulting firm that specializes in the use of advanced analytics to better inform strategic and operational decision making.

• Business Intelligence Services:• Predictive Analytics and Data Warehousing

• Student Success Analytics• Data Modeling, Integration, Management

• Regulatory and Benchmark Reporting Services:• VFA, CCA, AtD, State Reporting, etc.

• Strategic Services: • BI Readiness Assessments, BI Strategic Planning• Preparing for a Data Informed culture

Why Team with ASR?• Extensive experience in Higher Ed BI• Comprehensive predictive analytics

capabilities with a cadre of business intelligence tools/skills

• Tool/Technology Agnostic

For more information visit:www.asranalytics.com