# Presentation: 326704

## Data Strategy Overview

- Keith Wilson

***Session 15***

## Data Strategy Purpose

***The Right Data to the Right People at the Right Time.***

- Consolidation of Data into Shared Source
- Focus on Data Quality

- Standard Student Identification Method
- Trading Partner Management
- Routing ID
- Access Management

- Integrated Student View
- Integrated School View
- Foundation for more Timely and Efficient Processing

## Data Strategy Summary

-   Gather _**Desired Outcomes**_ and _**Current State**_
-   _**Create**_ the _**Target Vision**_ for Enterprise Data Usage
-   _**Facilitate**_ Paradigm Shift from _**Current to Target State**_

## Data Strategy Desired Outcomes

_**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 of a _Quality Assurance and Implementation Plan_
_**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_

***The Data Strategy defines FSA’s enterprise data vision for how it will combine tools, techniques and processes to handle its enterprise needs.***

## Data Strategy Initiatives

_**Data Framework**_
- As-Is and Target State Data Flows
- Data Quality Mad Dog and Quality Assurance Strategy
_**XML Framework**_
- XML ISIR
- XML Registry and Repository
_**Common Identification**_
- Standard Student Identification Method
- Routing ID
_**Trading Partner Enrollment and Access**_
- Single Sign-up
- Single Sign-on
_**Technical Strategies**_
- FSA Gateway

*Right Data*

*Right People*

*Right Time*

## Data Quality Methodology	

**Data Quality “Mad Dog”**highlights the high priority data quality issues facing FSA data owners and users.
**Data Quality Assurance Strategy**plan 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

***Improving Data Quality results in better information enabling better decisions.***

## XML Framework

- _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.

- FSA will use XML, via a single set of enterprise and community standards, to simplify and streamline data exchange across postsecondary education.

## Standard Student Identification Method (SSIM)

***The Standard Student Identification Method seeks to establish a simple framework by which FSA and Delivery Partners can consistently identify students/borrowers across all phases of the Student Aid Lifecycle.***

**Three-Pronged SSIM Solution:**
- Each part leverages effective, proven identifier solutions already being used in some parts of the
- FSA lifecycle.  Roll-out of these tools and processes consistently shall tighten controls and
- improve data integrity/consistency.
- _Primary Identifier Verification with the Matching Algorithm_
- _Additional SSA Verification:_
- _Consistent Correction Processing and Error Notification_

- Unique customer records can be inappropriately merged creating privacy concerns.
- A customer’s records cannot be linked appropriately preventing FSA from viewing data about a customer across all phases of the lifecycle.

**Key Identification Problems in the Current Environment **

## Single Sign-Up / Sign-On

## Technical Strategies:  FSA Gateway

- Enable trading partners to discover FSA capabilities by consolidating information and providing uniform access
- Provide right-time access to FSA data and business functions
- Leverage standard data formats in data exchange
- Use common data definitions for data exchange and validation
- Integrate with existing FSA capabilities and other initiatives
- Incorporate with Trading Partner Management and security efforts to enable uniform communication between FSA and trading partners

## Data Strategy Key Findings To Date

- _Data_ should be _organized by business process_, _not_ by _system_.
- “As-Is” Data Flow _Discussions_ have _facilitated a broader understanding_ of End-to-End _Business Processes_ across all FSA program areas.
- _Verified_ that using a _Matching Algorithm_ with _SSN, First Name, Last Name, and DOB_ is the most _flexible and tolerant_ way to _identify customers._
- Need to develop an _single Enterprise solution_ for all _Trading Partner Identification and Access_.
- Providing _data access_ to business experts is the _key component of improving_ the enterprises’ ability to make informed _business decisions._

***The Data Strategy teams have confirmed several key findings.***

## More Detailed Information

**For More Information Regarding the Standard Student Identification Method**** **
- Please attend the SSIM Breakout Session
- November 4	1:30 – 2:45
- November 5	10:45 – 12:00

**For More Information Regarding Single Sign-Up / Single Sign On**
- Please attend “A Session with a Twist: Whatever Happened to Single Sign-on”
- November 4	1:30 – 2:45
- November 5	1:30 – 2:45

## Technical Assistance

- I appreciate your feedback and comments.  I can be reached at:
- Email: Keith.Wilson@ed.gov