FSA Data Strategy

1. FSA Data Strategy Paul Hill Senior Technical Advisor Federal Student Aid Keith Wilson Project Manager for FSA Data Strategy Federal Student Aid May 26, 2004

2. Data Strategy Purpose Develop an overall approach towards data to ensure that accurate and consistent data is available to and exchanged among FSA and our customers, partners, and compliance and oversight organization.

3. Data Strategy Purpose “The Right Data to the Right People at the Right Time.” • Enterprise Standard for Student Identification • Integrated Partner Management • EnterpriseRouting ID • Enterprise Access Management • Integrated Student View • Integrated School View • Foundation for more Timely and Efficient Processing • Consolidation of Data into Shared Source • Focus on Data Quality

4. Data Strategy in the Press “The Right Data to the Right People at the Right Time.” From the January 2004 issue of “The Greentree Gazette” “ FSA’s Data Strategy Initiative is likely to have a significant impact on FSA’s ability to serve its customers. Its objectives include an enterprise-wide policy for managing and storing data and an industry-wide standard for publication and dissemination. FSA Staff commonly refers to the critical nature of ‘getting the right data to the right people as the right time.”

5. Data Strategy Desire Outcomes The Data Strategy defines FSA’s enterprise data vision and strategy for how it will combine tools, techniques and processes to handle its enterprise data needs. • Cross-Program Integration • Business objective gathering sessions comprised of cross-channel business owners and the establishment of Standard Identifiers for Students and Schools • Improved Data Quality • Through the execution of a Data Quality Mad Dog and the creation and execution of a Quality Assurance and Implementation Plan

6. Data Strategy Desire Outcomes • Improved Organization and Distribution of Data • Creation of an XML Framework and Internal and External Data Exchange Strategy • Establish a Data Storage Strategy • Data Warehouse and Data Mart Strategy • Plan for organizing data to answer broader, deeper business questions • Establish aTarget Visionfor FSA • Develop and refine a conceptual business and data architecture that outlines a Target State Vision for the FSA Enterprise

7. Data Strategy Initiatives Data Strategy has evolved into the integration of five core initiatives. • Data Framework • As-Is and Target State Data Flows • Refine Target State Vision • Data Quality Mad Dog • Develop Quality Assurance Strategy • Implement Data Quality Assurance Strategy • XML Framework • Develop XML ISIR • Develop XML Registry / Repository • Production Deployment of XML Registry / Repository Right Data Plain text bullets are initial Data Strategy Scope. Italics represent Data Strategy 2.0 scope. 6

8. Data Strategy Initiatives • Common Identification • Standard Student Identification Method • Routing ID • Trading Partner Enrollment and Access • Enrollment and Access Management • Technical Strategies • Data Storage, Web Services, Web Usage and FSA Gateway • Web Consolidation Options • Enterprise Analytics Architecture and Operating Guidelines Right People Right Time Plain text bullets are initial Data Strategy Scope. Italics represent Data Strategy 2.0 scope. 7

9. Data Strategy Approach Vision Target State Gather Business Objectives Strategic Focus Target State Refinement Target State Draft Data Strategy Roadmap Implementation Plan Current State As-Is Data Quality Discussions Data Strategy Team Findings And Input • Gather Desired Outcomes and Current State • Create and Refinethe Target Vision to reflect Enterprise Data and Process Usage • Facilitate Paradigm Shift from Current to Target State

10. Current State Confirmation Entity Flow Current State Overview Data Flow

11. Awareness Application Origination Disbursement Servicing Institution Servicing Aid Awareness & Application Delivery cycle Phase Life- Participation Application Origination & Disbursement Common Services for Borrowers Process Applicant/ Borrower Aid Education Submission Eligibility Repayment Consolidation Collections Student Aid on the Web Inbound Payment Processing Default Aversion Call Centers Application Processing - Electronic Processing - Paper Processing & Fulfillment Award Processing Consolidations Performance Mgmnt* School Payments (Pass-Through) - Student Based Pymnt Calcs - Payments & Tracking Loan Assignment Processing EAI Death, Disability & Bankruptcy Applicant/Recipient Eligibility - Electronic Processing - Paper Processing/Fulfillment Enterprise Delinquency Mgmnt Application Disbursement Processing Integration Accounting ITA Funding Level Management - Award Processing - Calc & Monitor Funding Chngs Integrated Collections Borrower Refund Processing Technical Architecture Performance Mgmnt* VDC Common Services for Borrowers Origination & Disbursement Virtual Data Center Award & Disbursement P-Note Processing School Aid Payments & FSA Service Recovery & Funding Level Mgmt Student Authentication & Access Mgmnt Processing Loans Resolution Student Authentication & Access Mgmnt Partner Management Partner Partner Eligibility Trading Partner Management Enrollment & Oversight Application for Participation Oversight - Closed School Processing - Ongoing Monitoring - Risk Management - Oversight Reviews/Actions - Accountability For Funds - Default Rate Calculations Partner Eligibility Enrollment/Access Mgmnt Funds & Internal Financial Management Controls Participation Management Performance Mgmnt* FSA Gateway Schools Portal Financial Partners Portal Help Desk Bulk Payment Calcs - ACA Payments to Schools Partner Payment Processing Payments & Tracking Partners & Lenders Servicers Trading Guaranty Agencies State Agencies Schools (Lender Servicers) ( School Servicers) Support Functions Other External Partners Enterprise Performance Management - Contract Management - Acquisition & Planning Strategy - Performance Analytics & Reporting To-Be Financial ED Department of Education Aid Life Cycle Financial Management - Accounting - External Financial Reporting - Funds Control - Budget - Internal Controls Business Process Awareness - Counseling - Awareness Portfolio Data Management - Aggregated Recipient Data - Program Analytics & Reporting Partner Application DRAFT Internal Transfer Partner Process Trading High-Level Business View Origination & Oversight Disbursement Eligibility Participation Oversight Monitoring Management Evolution to the Target State Vision A target state outlines the vision to achieve integration. Enterprise Analytics and Research Case Tracking Recommend Acquisition & Enterprise Performance Analytics (Ombudsman) Policy Changes Planning Strategy Management Audit Send/Receive from Matching Agencies Generate/Distribute ISIR/SAR Credit Check Transfer Monitoring Process Promissory Notes Servicing Reporting (FFEL & Campus Based) SSCR Enablers History Common Data Architecture NSLDS Functions Enterprise Shared Enterprise Shared Functions FMS Trading Students Warehouse/Data Marts Partners Transactions Distribute Eligibility Computation Edits - EFC RID Mappings Authentication & Access Management Partner Payment Calculation/PrePopulation CDR SSIM Logic Match Against CDA (FAH) Edit Checks Application Establish Consolidate Aid Aid Eligibility Person CSB Loans Awareness Determination Record Authentication & Access Tools Application Relationship Process Mgmt Business Intelligence Tools Payment Partner Payment State Agency Partner Payment Management Processing Admin Funding Ancillary Services Process External Financial GL AR Management Budgeting Payments Reporting Accounting FMSS GAPS Business Function External Transfer FSA Integration Vision Framework FSA Business Architecture FSA Enterprise Target State Business architecture drives technology solution.

12. Business Process Focused Business: System Focused Target Data: Unique Integrated Cost: Implement Lower, Operate Higher Implement Higher, Operate Lower Data Integration Strategy Determine overall Data Integration Strategy by considering a Business Process and Data Integration Continuum. Stand Alone Common Data Shared Source Common Access Features Independent solutions No automated sharing of information Sharing only possible through one-off efforts to integrate for analysis & research Independent solutions Sharing of information for analytical purposes in transactional system acting as a warehouse Enterprise data, metadata, and business rules integrated in one database Business process and application workflow centrally controlled Operational Data Store (ODS) used to feed DW Common data and methods shared via Data Access Objects (DAO) or Web service Single System Integrated Application Suite and Data 11

13. Target State Vision 12

14. Data Quality Mad Dog and Methodology Improving Data Quality results in better information enabling better decisions. • Data Quality “Mad Dog”highlights the high priority data quality issues facing FSA data owners and users • Data Quality Assurance Strategyplan for the continual improvement of FSA data quality and the maintenance and refinement of data across the enterprise • Key Concepts • Fewer data stores = less redundancy • Standardized Definitions and Terminology via XML Framework

15. XML Framework FSA will use XML, via a single set of enterprise and community standards, to simplify and streamline data exchange across postsecondary education. Benefits • Data Exchange Standard – Standardize FSA’s data exchange using XML as the data exchange technology standard. • Consistent Accurate Data – The framework will define data standards, as XML Core Components, for data exchange to achieve consistent and accurate data. • Data Cleanup and Maintenance – Enable data cleanup and maintenance activities. • Standard Data Tools and Processes – Establish standard data tools and processes, to support consistently performed data/XML modeling. • System Flexibility – Provide system flexibility to simplify future interface changes and support new application and data exchange requirements, through XML-based data modeling. 14

16. Technical Strategies Internal Data Exchange The way in which internal systems transmit and receive data with one another, including the type/format of data exchanged: Qualities and Features: • Improve business services accessibility • Enable standards based access and communications

17. Technical Strategies Web Usage (Portals) Customer experience and data exchange through the Students Portal, Schools Portal, Financial Partners Portal and other FSA websites: Qualities and Features: • Access - The individual user groups’ ability to access various FSA websites and the login features that provide a unique user experience. • Content Presentation – The FSA websites’ patterns for design layout and navigational structure including the use of graphics, links, fonts and colors. • Content Management – The publication and distribution of web content including customization, personalization and search capabilities. • Technical Architecture – How the FSA supporting architecture enables web content delivery through Web Application Servers and facilitating Web Services.

18. Technical Strategies • Web Services • Software components that use open standard communication protocols to interact with other applications over the Internet for service orientated architectures: • Qualities and Features: • Provide a straightforward, low entry cost mechanism for system-to-system interaction between trading partners • Based on a set of industry standard protocols and technologies available on all platforms • Support the reuse and extension of existing components/applications

19. Technical Strategies • External Data Exchange (FSA Gateway) • The means by which FSA extends Enterprise data and business capabilities to trading partners: • Qualities and Features: • Extending FSA Enterprise data and business capabilities to the external community • Provide single virtual entry point for exchanging data with external trading partners

20. Data Marts Technical Strategies Data Storage, Management and Access The technical components and business processes that define the ability to collect, analyze, access and disburse data: Qualities and Features: • Data Architecture – The technical enabler for data storage, management and access to enterprise information. • Data Warehouses – A collection of data designed to support enterprise data relationships. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. • Data Marts – A database or collection of databases, designed that contain a “slice” of data for a specific business view or purpose. • Data Mining– Database applications that facilitate data investigation and pattern discovery. • Data Analytics – The process of analyzing different dimensions of data to facilitate forecasting and trend analysis. Business Intelligence Data Analytics Data Mining Data Warehouse Data Architecture

21. Data Strategy Key Findings To Date The Data Strategy teams have confirmed several key findings: • Datashould be organized by business process, not by system. • Providing data access to business experts is the key component of improving the enterprises’ ability to make informed business decisions. • Verified that using a Matching Algorithm with SSN, First Name, Last Name, and DOB is the most flexible and tolerant way to identify customers.

22. Data Strategy Key Findings To Date • Need to develop an single Enterprise solution for all Trading Partner Identification and Access. • “As-Is” Data Flow Discussions have facilitated a broader understanding of End-to-End Business Processes across all FSA program areas.

23. Data Strategy 2.0 • Gathered Business Objectives • Drafted Target Data Flows • Created a Vision of “What it should look like” Where We Are

24. Data Strategy 2.0 What We Need To Do • Explore options for new questions raised during Target Vision Discussions and Retreats. • Implement XML Registry / Repository of Core Components to the Internet. • Enact the Data Quality Assurance Methodology for the Enterprise.

25. Data Strategy 2.0 Functional Gap Activities 24

26. Data Strategy 2.0 Deployment Activities • Deploy XML Registry / Repository to the Internet • Makes FSA standardized Title IV Aid definitions and Core Components available for both FSA and Community usage. • Provides a vehicle to drive consensus on data standards. 25

27. XML at FSA • Technological Advantages • Extensible – easily increased or decreased • Technology neutral • Decoupled – easily changed • Standards - Community Participation • Non-Proprietary • Increase Data Quality

28. Common Record: ISIR • Award Year 2005-06 • XML and Flat file available from CPS • Award Year 2006-07 • Current plans for Award Year 2006-07 are XML Only

29. Documentation • Information for Financial Aid Professionals (http://www.ifap.ed.gov) • SAR/ISIR Reference Materials • Award Year 2004-05 • Draft ISIR Schema, Sample Document, and Record Layout

30. FSA Future Plans • Future CPS Development • XML Framework 2.0 • Analyze remaining suite for Award Year 2006-07 implementation • CPS Business Process Changes * School Sign up • Via Participation Management • Receive Flat file or XML • Default is Flat file • Change from XML to Flat file at anytime and vice versa • EDExpress will only process CommonRecord: ISIR * All changes apply to States.

31. FSA Future Plans • ISIR Datamart Requests • Can request different output than listed as school preference • XML users can request: • ALL data • Submission/Eligibility only • Financial aid history only

32. 2004 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV COMPLETED STRATEGY DATA FRAMEWORK TECHNICAL STRATEGIES TARGET VISION FFEL AND STUDENT ENROLLMENT DATA FLOW ANALYSIS TARGET VISION ENTERPRISE ANALYTICS ARCHITECTURE ANALYSIS CSB ALIGNMENT XML MANAGEMENT XML CORE COMPONENT DICTIONARY R2.0 TARGET VISION COMMON DATA ARCHITECTURE OPERATING GUIDELINES TARGET VISION FUNCTIONAL GAP ANALYSIS XML REGISTRY/REPOSITORY PRODUCTION READINESS TARGET VISION WEBSITE/PORTALS CONSOLIDATION/SHARED SERVICES ANALYSIS XML REGISTERY/REPOSITORY PRODUCTION SUPPORT DATA QUALITY MANAGEMENT DATA QUALITY MANAGEMENT SUPPORT Data Strategy 2.0 Schedule 31

33. Contact Information We appreciate your feedback and comments. We can be reached at: Paul Hill Phone: (202) 377-4323 Email: Paul.Hill.Jr@ed.gov Keith Wilson Phone: (202) 377-3591 Email: Keith.Wilson@ed.gov