Once Upon a Time: The Story of a Successful BI Implementation

Slides:



Advertisements
Similar presentations
Enrollment Management Unified Report (EMUR) Indiana University of Pennsylvania Jeff Montgomery.
Advertisements

Care and Feeding of a Data Warehouse
Pennsylvania BANNER Users Group 2006 Integrate Your Decision Support with Cognos 8.
1. 2 August Recommendation 9.1 of the Strategic Information Technology Advisory Committee (SITAC) report initiated the effort to create an Administrative.
Desire2Learn Advanced Learning Analytics Ronald Mol Desire2Learn
Business Intelligence
Copyright Dickinson College This work is the intellectual property of the author. Permission is granted for this material to be shared for non-commercial,
PeopleSoft EPM & OBIEE Data Warehouse Reporting Project Update Wednesday, April 11, 2012 Tejune Kang, Jen Drake (ITS)
Building a Self-Service Business Intelligence System for Strategic Decision-Making Oyebanjo A. Lajubutu, Ph.D. Director of Institutional Research and Assessment.
Business Intelligence Technology and Career Options Paul Boal Director - Data Management Mercy ( April 7, 2014.
UNCLASSIFIED Business Intelligence and SharePoint 2010 Steve McDonnell.
DASHBOARDS Dashboard provides the managers with exactly the information they need in the correct format at the correct time. BI systems are the foundation.
Data Warehousing: Defined and Its Applications Pete Johnson April 2002.
GLOCO Enterprise Measurement System Team 4 John Armstrong Ananthkumar Balasubramanian Emily James Lucas Suh May 5, 2012.
5.1 © 2007 by Prentice Hall 5 Chapter Foundations of Business Intelligence: Databases and Information Management.
Lori Smith Vice President Business Intelligence Universal Technical Institute Chosen by Industry. Ready to Work.™
- 1 - Roadmap to Re-aligning the Customer Master with Oracle's TCA Northern California OAUG March 7, 2005.
INTRODUCTION TO DATA MINING MIS2502 Data Analytics.
Data Warehouse Overview September 28, 2012 presented by Terry Bilskie.
ETL Overview February 24, DS User Group - ETL - February ETL Overview “ETL is the heart and soul of business intelligence (BI).” -- TDWI ETL.
1 Business Intelligence in the Information Age © 2006 Acxiom Corporation. All Rights Reserved. Carmen McKenna-McWilliams Marketing Technology Center of.
MA Educational Data Warehouse Project MADOE and School District Collaboration Maureen Chew MADOE MA Digital Govt Summit 12/11/2007.
 Business Intelligence Anthony DeCerbo Meaghan Duffy Steve Smith Warren Scoville.
CS 157B: Database Management Systems II April 3 Class Meeting Department of Computer Science San Jose State University Spring 2013 Instructor: Ron Mak.
12/4/ OBIEE Technical Conference Getting Started with a Dashboard Development Project Theresa May.
Rajesh Bhat Director, PLM Analytics Applications
Presenter : Ahmed M. Mosa User Group : SQLHero. Overview  Where is BI in market trend  Information Overload  Business View  BI Stages  BI Life Cycle.
CS 157B: Database Management Systems II April 10 Class Meeting Department of Computer Science San Jose State University Spring 2013 Instructor: Ron Mak.
1 Copyright © Oracle Corporation, All rights reserved. Business Intelligence and Data Warehousing.
(OBIA) Training & Placement Program By Keen IT To request free demo session please mail us at
REPORTING AT THE UNIVERSITY OF CHICAGO AUGUST 20, 2010.
Cognos BI. What is Cognos? Cognos (Cognos Incorporated) was an Ottawa, Ontario-based company that makes Business Intelligence (BI) and Performance Management.
What is the future of OFA?. Bryan Eckle FullNorth Technology Group Provide expert resources for Oracle Applications and Business Intelligence from scoping,
Banner Project Overview February 24, Presentation Objectives:  What is the Banner Project ?  When are we doing it ?  How will we do it ?  Who.
Business Intelligence Overview
Workshop 4: Developing a one page business case
Create a system that reflects higher education best practices
The BI360 Business Intelligence Suite
How Arizona State University Moves Data Faster
Presented by: Dr. Jan I Fox, Marshall University
Raising your BI IQ—How Business Intelligence Impacts IR
Still a Toddler but growing fast
Leveraging the Business Intelligence Features in SharePoint 2010
Decision Support Systems
Student and Financial Aid Systems Transformation Project
Business Intelligence & Data Warehousing
Gabe Cano, Altarum Institute  Mark Perry, Altarum Institute 
IBM Tivoli Web Site Analyzer Training Document
Welcome! BI Executive Sponsors October 13, 2015
Chapter 13 The Data Warehouse
Hyper-V Cloud Proof of Concept Kickoff Meeting <Customer Name>
Add intelligence to Dynamics AX with Cortana Intelligence suite
Moving the Needle Conference 2017
Business Intelligence
Bus06 - Business Intelligence in the Public Sector
Data Warehouse Overview September 28, 2012 presented by Terry Bilskie
DAT381 Team Development with SQL Server 2005
Data Visualizations using Blackboard Analytics and Tableau
Introduction of Week 9 Return assignment 5-2
Employee engagement Delivery guide
Alice Faraone, Villanova University Dan McGee, Villanova University
Data Warehousing Concepts
Agenda Purpose for Project Goals & Objectives Project Process & Status Common Themes Outcomes & Deliverables Next steps.
Business Intelligence & SharePoint
Data Governance at UMBC: Built from the Bottom Up
Analytics, BI & Data Integration
Jet Global Solutions Overview
David Gilmore & Richard Blevins Senior Consultants April 17th, 2012
Implementing a Distributed Enterprise Architecture to Deliver BI
Presentation transcript:

Once Upon a Time: The Story of a Successful BI Implementation Lisa Newman, Senior Software Engineer Rachael Coombes, Business Intelligence Specialist

About Wellesley College Liberal arts women’s college founded in 1870 Located in Wellesley, MA (12 miles west of Boston) Enrollment of ~2300 students Offers 56 different majors 7:1 student-faculty ratio

Presentation Agenda Goal: Agenda: Share strategies for developing a Business Intelligence (BI) implementation plan for purchased solutions Agenda: What is Business Intelligence? Business Analytics demo (Pyramid Analytics) Where we are and how we got here Successes and challenges

Defining Business Intelligence TDWI: “Business intelligence (BI) unites data, technology, analytics, and human knowledge to optimize business decisions and ultimately drive an enterprise’s success.”1 Started with this BI definition: Self-Service Business Analytics Data Driven Decision Making Transitioned into including this in BI definition: Operational Reporting 1 The Data Warehousing Institute (TDWI): https://tdwi.org/portals/business-intelligence.aspx

Audience Poll What stage of BI Implementation are you in? Exploring the potential of BI Just starting Technical implementation: at least one content area Functional roll-outs: users are actively using the BI analytical/reporting tools If your Institution has a BI system… …is it a purchased solution? …is it a custom built system?

Purchased BI Solution: Blackboard Analytics (BBA) BBA modules implemented: Student, Admissions, Financial Aid and Finance Optimized & structured for analysis/reporting: slicing, dicing, drill up/down, roll-ups, etc. Contains data architecture and data structures that allow for multi-dimensional analysis Descriptive analytics “The first stage of business analytics is descriptive analytics, which still accounts for the majority of all business analytics today.[5] Descriptive analytics answers the questions what happened and why did it happen. Descriptive analytics looks at past performance and understands that performance by mining historical data to look for the reasons behind past success or failure.” (https://en.wikipedia.org/wiki/Prescriptive_analytics) “The next phase is predictive analytics. Predictive analytics answers the question what will happen. This is when historical performance data is combined with rules, algorithms, and occasionally external data to determine the probable future outcome of an event or the likelihood of a situation occurring.” (https://en.wikipedia.org/wiki/Prescriptive_analytics)

Analytical/ Reporting Purchased BI Solution Banner Database (Oracle) Data Warehouse (SQL Server DB – Star Schema design) OLAP Cubes (SQL Server Analysis Studio) Analytical/ Reporting Toolsl Extract Process Transform Logic Centralized Data Definitions Blackboard Analytics Processing: 1. Source data extracted from Banner DB to Data Warehouse DB 2. Data Transformed (business rules) from staging into final tables 3. Processed into cube designed to facilitate multi-dimensional analysis

(Business Analytics Demo) Data In Action (Business Analytics Demo)

Screenshot of Demo

BI Implementation: Business Focused Business focused project, not a technology-centered project Understanding the data and the business needs: now and forthcoming Actionable, dynamic and accessible data "Framing" BI Project Can be a significant culture change. for Business Users

Key Project Areas Sponsorship & Championing Project Data Definitions & Customizations Data Governance & Data Quality Dashboard Roll-outs User Adoption & Looking Forward

Student Implementation Overview 2012 2013 2014 2015 ∙ BBA Student install ∙ Data Definitions ∙ Gap Analysis ∙ Data Verifications ∙ BI Advisory Committee ∙ Project name: WANDA ∙ Data Definitions ∙ Customizations ∙ Data Verifications ∙ Data Quality ∙ Data Workflows ∙ Analytical Tool Assessment ∙ Training Agile PM ∙ Pyramid usage ∙ Prototypes ∙ IR and Admissions Roll-outs ∙ SSRS install ∙ On-going data definitions training ∙ Customizations ∙ Data Quality ∙ Dashboard Roll-outs: Faculty, Academic Depts., Humanities, etc. ∙ Upgrade Student ∙ BBA FinAid install ∙ Data Governance ∙ Pyramid upgrade ∙ SQL Server upgrade

Student Implementation Timeline (2013) FUNCTIONAL TECHNICAL

Sponsorship & Championing Project Project name: WANDA Wellesley ANalytics Decision-Support Applications Finding partners on campus

Data Definitions & Customizations Centralized Data Definitions Creating customizations for BBA standard definitions “One source of the truth” Example: What is an Enrolled Student? On-Campus? Study Abroad? Matrics? Non-Matrics? Etc. Asking users to adopt a different truth (in comparison to their own records)

Data Governance & Data Quality Data Governance structure: - WANDA Advisory Committee - Functional Working Groups - Technical Working Groups Security Policies: Data Access Data Quality: roles of Data Custodians and Data Stewards Census Snapshots Security Data Matrix (example)

Dashboard Roll-outs Be flexible in your training methods User documentation, group sessions, 1-on-1 deskside training Build prototypes and interactive dashboards Get people excited about data early on!

User Adoption & Looking Forward Once you have something people like, it explodes!

Reminder: Complete your session evaluations by April 8th Contact Information Lisa Newman Senior Software Engineer lnewman@wellesley.edu Rachael Coombes Business Intelligence Specialist rcoombes@wellesley.edu Reminder: Complete your session evaluations by April 8th