Enterprise Data Architecture - PowerPoint PPT Presentation

Loading...

PPT – Enterprise Data Architecture PowerPoint presentation | free to download - id: 422ba4-ZDFlM



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Enterprise Data Architecture

Description:

Changing Data Standards from Wall Street to DC & Beyond John Mulholland Vice President for Enterprise Data Fannie Mae February 29, 2012 * | Confidential - Internal ... – PowerPoint PPT presentation

Number of Views:510
Avg rating:3.0/5.0
Slides: 16
Provided by: RamRamac
Learn more at: http://assets.en.oreilly.com
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Enterprise Data Architecture


1
Changing Data Standardsfrom Wall Street to DC
Beyond
John Mulholland Vice President for Enterprise
Data Fannie Mae February 29, 2012
2
Agenda
  • Impetus for Change
  • Technology Maturity Comparison
  • Current State
  • Future State
  • Roadmap to Success
  • The Balance
  • Challenges Opportunities
  • Changing the Industry Fannie Mae Leading Change

3
Impetus for Change
Turmoil in the financial industry has created a
need for greater transparency
2007-Investment Banks, Bear Sterns Lehman
Brothers Collapse
2008-Goldman Sachs Morgan Stanley abandon their
status as investment banks
2010-Dodd-Frank Wall Street Reform and Consumer
Protection Act
2008-Banks received 700B TARP funds
2008
2009
2010
2007
2011
Early 2010, Fannie Mae launches enterprise-wide
data management program
Fannie Mae deploys new capabilities in data
controls begins streamlining data infrastructure
On September 7, 2008, James Lockhart, director of
the Federal Housing Finance Agency (FHFA),
announced that Fannie Mae and Freddie Mac were
being placed into conservatorship of the FHFA.
Wall Street to DC
Digitization
Data Mining
Innovation
Semantics
Business Intelligence
Industry Standards
Proactive Data Quality
The push to manage enterprise data is often a
result of external forces
4
Maturity of Mortgage Industry a Comparison
Airline Industry near real-time tracking of all
flights
Credit Card Industry American Express can detect
fraudulent activity based upon your spending
habits in near real-time, often denying charges
on the spot
The mortgage industry lags other industries in
technology innovation
5
Maturity of Mortgage Industry a Comparison
(contd)
Other industries can track data near real-time,
but our partners in the mortgage industry have
difficulty tracking the status of their loans in
real-time
  • Secondary Mortgage Market
  • Buried under paper
  • Manual processes
  • Minimal automation

The mortgage industry lags other industries in
technology innovation
6
Current State
Current State infrastructure is complex and lacks
automation.
Legacy point-to-point interfaces create
unnecessary complexity
7
Future State
Future State infrastructure enables
straight-through processing and offers
operational efficiencies.
Trusted Sources of Data
Data should be trusted as it flows with the
proper data management controls
8
Roadmap for Success
Multi-year planning and funding required for
execution
  • Constant focus on business value and innovation

Continually Improve
  • Data Management practices become a part of the
    fabric of the company
  • Continue to build and refine target state
    enterprise capabilities
  • Continuous improvement and future readiness
  • Focus on innovative technology solutions
  • Establishes business accountability
  • Focuses on critical data needed to be managed at
    enterprise level

Execute Integrate
  • Integrate data management practices into
    development process
  • Focus on greatest business value
  • Adapt solution and reduce technology footprint
  • Embed target state enterprise capabilities in
    business

Build Foundation
  • Implement data management tools to focus on data
    quality, metadata, and data security
  • Build enterprise-wide data governance processes
  • Integrate data governance, data quality,
    metadata, and data security practices
  • Defines plans for enterprise

Define Design
  • Define Enterprise Data Management strategy
  • Design enterprise data architecture

Iterative execution must be tied to business value
9
The Balance
The triangle of people, process, and technology
is fundamental and requires equal investment for
success
People
Managing people and culture change
Data---gtInformation
Creating and Integrating Processes
Enabling the business and innovation
Technology
Process
Managing the challenges across people, process,
and technology is critical for change
10
Challenges People
Opportunity
Challenge
Invest in a strong Data Governance program
Lack of accountability
Put the right people in the right seats
Lack of skills
Data hoarding
Data is an enterprise asset
Resistance to change
Executive level support
Changing behavior requires a broad change
management approach
11
Changing Organizational Structures.
Cathryne Clay Doss of Capital One was appointed
Chief Data Officer in 2003 Wikipedia
Dr. Usama Fayyad, Chief Data Officer and Sr. Vice
President of Yahoo!, was one of the first people
known to officially hold this job title Wikipedia
Citi was the first in the finance industry to
name a Chief Data Officer 2007
The role of Chief Data Officer emergesits
crucial to have a C-level person who is
responsible for crafting and implementing data
strategies, standards, procedures, and
accountability policies at the enterprise level.
Information Management 2008
Bank of America Names John Bottega Chief Data
Officer December 2011
12
Challenges Process
Opportunity
Challenge
Enforce enterprise-wide data standards
Lack of data standards
Siloed processes
Enterprise-level process integration
Integrate within software development and
architecture review processes
No integration with development process
The implementation and integration of
enterprise-wide processes requires constant focus
and attention from top executives
13
Challenges Technology
Opportunity
Challenge
Data silos
Consolidated trusted sources
Data volumes and velocity
Data optimization and scalability
Simplify data architecture
Complex data architectures
Services-based architecture
Real-time enterprise requirements
Lack of straight-through processing
Automated controls and monitoring
Structured and unstructured data (email, video,
logs, system events etc)
Leverage Big Data solutions
The mortgage industry needs to focus on
technology innovation
14
Technology for enterprise-wide data mgmt
15
How we are changing the industry..
Industry Standards
Servicing Alignment Initiative
Uniform Loan Delivery Dataset
Secondary Market
Primary Market
Enhanced Analytics
Predictive Models
Fannie Mae
Proactive Data Quality
EarlyCheckTM
Mortgage Industry
Fannie Mae is improving our internal practices
while moving the industry forward
About PowerShow.com