Data Warehouses and Dashboard – A Primer Mr. Tod R. Massa Director, Policy Research & Data Warehousing, State Council of Higher Education for Virginia Dr. Dave Oehler Director of Assessment, Information and Analysis, Northwest Missouri State University

5/10/20052 Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/20053 Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/20054 What is a Data Warehouse?  Definition/use:  A repository of data, frozen in time  Scrubbed/cleansed  Some portions captured “as is”  Some portions massaged to facilitate faster computation/reporting

5/10/20055 Goals of Data Warehousing GOAL 1: Accessible information  Intuitive and self-describing  Labeled appropriately  “Slicing and dicing”  Minimal wait times

5/10/20056 Goals of Data Warehousing GOAL 2: Consistent information  Carefully collected from multiple operational sources  Cleansed and quality assured  Common definitions  Unique describing labels

5/10/20057 Goals of Data Warehousing GOAL 3: Flexible during change  Designed to handle change  Avoids invalidating existing data  Minimal disruptions in existing applications and data  Accountable for changes

5/10/20058 Goals of Data Warehousing GOAL 4: Secured information  “Crown Jewels”  Usually contains sensitive business information  Must effectively manage access

5/10/20059 Goals of Data Warehousing  GOAL 5: Improved decision-making  Data needed to make decisions  Supply evidence to improve decisions  Decision Support System

5/10/ Goals of Data Warehousing GOAL 6: Accepted among the organization  Extent of deployment after training  Meeting the needs of management  Use of system to make business decisions

5/10/ Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/ Components  Operational source systems  Student information systems  Financial information systems  Alumni information systems  Human resource information systems  Other shadow information systems

5/10/ Components - Operational Data Store  Elements Considered  Existing reports  Existing dashboard displays  Future research interests  Collection cycles  Census  End of Term  Completions  Cleanse Data  Including codes/descriptions  Converting/Keeping operational code values  Data similarities  storage structure  reporting usage  Documentation

5/10/ Components  Data staging area (ETL)  Extract  Collect data records from operation information systems  Transform  Massage data records (cleanse, combine, de- duplicate)  Load  Populating data records in the warehouse

5/10/ Components  Data presentation  Area accessible by management  Integrated data marts (common dimensions and facts)  Usually presented, stored, and accessed through dimensional schemas  Contains detailed atomic data  Operational by management

5/10/ Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/200517

5/10/200518

What is measured gets noticed What is noticed gets acted on What is acted on gets improved This and the following slide were adapted from a Dee W. Hook presentation. Phenomenon of Measurement

5/10/ Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/ What is a Dashboard?  Definition/use:  Both a process and a tool  Looking for unfavorable trends or patterns and focusing energy on improving priority areas  A (diagnostic) means for monitoring performance to ascertain what is working well and where additional attention is needed  A few (4-6) sets of indicators, representing the most central areas related to high performance

5/10/ How Does a Dashboard Focus Activities and Processes?  Requires clear definition of outcomes  Focuses on a manageable (small) set of key outcomes (results)  Encourages cross-functional communication  Requires fact-based decision processes  Data reporting structures  Process improvement orientation  Layering of detail (summative vs. formative)

5/10/  Dashboards help you know what’s important  Dashboards focus on actions that make a difference  Collect data to create information you can use, then use it Time is Increasingly a Precious Resource

5/10/  Assessment needs to answer questions  Systems to collect, analyze, and report information need to be developed to support the specific information requirements Data for Decision-making

5/10/ Assessment System Design 1. Data Collection  Centralized measures  Decentralized measures 3. Reporting Systems  Summative Information  Formative Information 2. Data Processing  Disaggregation system  Aggregation system  No transformation 4. Analysis/Decision-making  Cabinet, Deans, Directors, Department Chairs  Department Chairs, Faculty

Data Collection Reporting Systems Analysis and Decision-making Centralized Decentralized Disaggregation System Aggregation System Summative Information (Dashboards, Profiles) Formative Information (Operational) Cabinet, Governing Board, External Audiences Directors, Department Chairs, Faculty, Staff No Transformation Deans, Directors, Department Chairs No Transformation Directors, Department Chairs Much Little Detail Data Processing

5/10/ Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/ What Metrics are in a Dashboard?  The Dashboard includes a balanced view of an organization  Learning and Growth (student academic progress; faculty and staff development, scholarship and research productivity)  Customer Relations (students, faculty, staff, alumni, parent satisfaction and involvement)  Internal Processes (functional area performance – accuracy, timeliness, friendliness)  Financial Measures (fiscal health and viability)

5/10/ Northwest’s Dashboard Model  Our model includes several types of information/report presentations  Dashboards – single screen current status  Trend charts – key data element trends over time  Data tables –key data detail trends over time  Majors, minors, advisees, degrees, SCH, financials  Special interest charts/tables

5/10/ Features of the Northwest Balanced Scorecard System  Dashboard “lights” to indicate current status  Hyperlinks to navigate through workbooks  Hyperlinks to “drill down” to detail  Comparative data links for setting targets  Real-time data updates  Accommodates various data sources  Modular design to facilitate upgrading  Automated updating of modules

5/10/ President’s Dashboard  General Dashboard categories:  Student Success  Satisfaction  Enrollment  Financials  Additional monitoring category:  Strategic Initiative Achievement

President’s Dashboard

5/10/ Provost’s Dashboard  General Dashboard categories:  Student Academic Performance  Student Satisfaction  Student Success and Placement  Academic Workload  Additional monitoring category:  Strategic Initiative Action Plan Progress

Provost’s Dashboard

5/10/ VP Student Affairs Dashboard  General Dashboard categories:  Student Engagement  Student/Stakeholder Satisfaction  Auxiliary (financial)

VP Student Affairs’ Dashboard

5/10/ Presentation Overview  Data Warehousing  Goals of data warehousing  Components of a data warehouse  Data flow  Dashboards  Goals of dashboards  Components of dashboards  “Drilling down”

5/10/ Comparative Data  In order to judge how good your performance is, results should be put into some context  Trends over time  Comparisons to other internal units  Comparisons with peer groups  Comparisons outside of the education sector

Better

5/10/ Interpreting Dashboard Indicators  To follow up on indicators of interest, use hyperlinks to access increasing levels of detail  Student satisfaction as an example  President’s dashboard to  Provost’s dashboard to  Noel-Levitz Student Satisfaction Inventory data trends

Praxis and C-BASE results module Major Field test results module Academic Profile results module Undergrad majors and minors, Graduate majors, Degrees, Advisees module Student opinionnaires of teaching module General Education local module Program SCH generation module Financial data module Placement data module EMSAS module (freshman success) Alumni satisfaction module Major field local/senior capstone module Department ‘A’ Profile and Dashboard College ‘A’ Profile and Dashboard Department ‘etc.’ Profile and Dashboard College ‘etc.’ Profile and Dashboard Provost’s Profile and Dashboard Service unit ‘A’ Profile and Dashboard Service unit ‘B’ Profile and Dashboard Service unit ‘C’ Profile and Dashboard Service unit ‘etc.’ Profile and Dashboard President’s Dashboard Provost’s Dashboard Metrics Architecture July 28, 2002 Comparative data for targets Student satisfaction module

5/10/ Data Warehouses and Dashboards – A Primer  Contact information:  Tod Massa  State Council of Higher Education for Virginia  (voice)   Dave Oehler  Northwest Missouri State University  (voice) 