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Unlocking Business Value: Enterprise Data Management strategies to increase
performance, cut risks, and control costs.
Today’s enterprise level IT departments are challenged to support the
highest levels of corporate performance within a strict budget. The risks
of information security, data retention and compliance loom large.
Enterprise data management strategies enable you to accelerate performance
while controlling costs and mitigating risks.
Princeton Softech is pleased to provide information on the following
Controlling Data Growth Through Database Archiving
Information is the most valuable asset in business today. Information is
required for all revenue generating transactions. As businesses expand,
the number of data transactions subsequently grows as well. A best
practice for controlling this data growth is to implement database
archiving, a key component of enterprise data management. Database
archiving enables you to archive and remove historical, inactive data from
the production database, and save that data to more cost-effective and
appropriate storage media. This reduces the amount of data on your Tier 1
production environment, improving performance immediately as well as
reducing the cost of purchasing additional expensive storage. Database
archiving maintains the “business and technical context” of the archived
data, so that the company can easily research and retrieve the required for
responding to a customer inquiry or audit request. Further, disaster
recovery as well as upgrades and migrations can all be performed quicker
and more efficiently.
Managing Test Data Effectively and Data Privacy in the Testing Environment
Reliable applications come from reliable testing – and realistic test data
plays a key role. Many organizations clone or copy production environments
to create test data – a time consuming and expensive approach. Subsetting
data enables you to extract the business objects or transactions you need
to create targeted test scenarios. You can extract data from a single
database or across multiple related databases and platforms. After
migrating data into the target environment, you can view multiple related
tables in a single display. Then you can easily edit your test data to
force error and boundary conditions needed to verify exception handling.
Reusable processing definitions help you speed iterative testing tasks and
ensure complete coverage.
Finally, learn how to sufficiently validate results. You can compare
results from a single database table or across sets of multiple related
tables. Make it easy to identify and resolve application problems
cost-effectively – before they impact your customers.
Gartner suggests that 70 percent of data breaches are internal to
corporations. Many organizations today focus only on implementing
strategies to protect data in the production environment, while leaving the
testing environment vulnerable. In this session, learn about appropriate
strategies for removing, masking and transforming data that can be used to
identify individuals in your testing environment. Understand how you can
create contextually accurate but fictionalized data to produce accurate
test results and support compliance with local, state, national,
international and industry-based privacy regulations.
Data Services IT Specialist
317-566-4608, T/L 554-4608
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