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Data Governance Conference
In Perspective Sessions
The
Future of Data Governance: Business Rules Monitoring and
Your Compliance Initiatives
Daniel Teachey
DataFlux
Each year, organizations worldwide face an ever-growing number of
compliance requirements. These initiatives - which arrive from external
or internal compliance pressures - require companies to develop
and maintain high levels of data quality and data integrity. This
presentation will give participants an overview of:
· The technologies available to improve compliance initiatives
· The emergence of business rules monitoring within data
governance efforts
· How the enforcement of business rules impact compliance
efforts
The Sensitive Data Discovery Revolution
Denise Sparks
Sr. Marketing Manger
Exeros
Where does sensitive data exist in your organization? Where is it
hiding, how does it flow through your systems, and who really has
access? If you think you know the answer, think again. In most companies,
recognized data is just the tip of the iceberg - hidden sensitive
lurks inside corporate applications, databases, development and
marketing systems, sales laptops, Web sites, and beyond. Undiscovered
sensitive data is prone to accidental exposure, intentional misuse,
and dangerous dissemination.
For the first time in 40 years, there is a software solution that
can find your sensitive data - or even pieces of your sensitive
data - wherever it is hidden in your systems. No matter what the
project spec or metadata tells you, Exeros DataMapper looks at the
actual data and discovers relationships between data elements in
different databases or applications. This presentation will explain
how the top credit card companies and investment banks are leading
the charge in the sensitive data discovery revolution.
Making Data Safe for Compliance and Outsourcing
David Friedland
VP Business Development
Innovative Routines International (IRI), Inc.
Where the rubber meets the road in protecting data at risk, there
are safer, faster and more cost-effective ways to get compliant
- and prove it. After data governance efforts have identified and
located sensitive data, you can now protect it
at the field level through:
· Encryption (and decryption)
· Custom Masking
· De-identification (and re-identification)
· Safe Test Data/File Synthesis
And what if you could also - simultaneously -
· Filter (and cleanse)
· Transform (sort, join, aggregate)
· Remap (calculate, convert, reformat)
· Report (and segment)
on huge volumes of data, outside the database -- without the cost
or complexity of ETL tools or encryption appliances?
IRI's
CoSORT, FAst extraCT and RowGen tools leverage
the same metadata - and usually, metadata you already have -
to simultaneously process, present and protect data. IRI will
demonstrate the possibilities with simple job scripts and logs.
Governing Large Data Landscapes
Arka Mukherjee, Ph.D.
Global IDs
Companies with large data landscapes (100+ databases) face unique
challenges in data management. The scale and complexity of evolving
data environments makes data governance and stewardship difficult,
and time consuming. CIO's and Enterprise Data Architects are faced
with the possibility of uncontrolled growth and disparity in their
data landscape, with escalating costs and negative perceptions from
customers.
This
presentation will discuss a step by step approach to managing large,
complex data environments, in a cost effective way. We will discuss:
·
The motivation and benefits of governing a complex business environment.
· What is feasible, and what is not.
· Why automation of core data governance tasks is key to
success
· A step by step approach to measurement, monitoring and
stewardship of large data landscapes.
· Dealing with organizational resistance
· Project Estimation Guidelines: Costs, Timelines, Team Structures,
Deliverables.
Data
Governance: Continuous, Measurable Data Improvement
Judy Ko
Senior Director Enterprise Marketing
Informatica
Enforcing
data governance requires the establishment and monitoring of key
data metrics to track the "fitness" of critical enterprise
data. Without concrete metrics, it is difficult to measure the effectiveness
of a data governance program, and to ensure visibility and accountability.
However, measuring data quality, availability, and auditability
is often a challenge. What to measure? How to do it? How to scale
it out on an ongoing basis? This session will cover:
·
Defining key data metrics
· Establishing baseline measurements
· Measuring and monitoring metrics on an ongoing basis via
scorecarding
We
will also discuss best practice approaches and enabling technologies
that can significantly increase the likelihood of success for data
governance programs.
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