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Data quality is an elusive subject that defies measurement
and yet is critical enough to derail any single IT project,
strategic initiative or even a company as a whole. The data
layer of an organization is a critical component because it
is so easy to ignore the quality of that data or to make
overly optimistic assumptions about its efficacy. Having
data quality as a focus is a business philosophy that aligns
strategy, business culture, company information, and
technology in order to manage data to the benefit of the
enterprise. Simply put, data quality is a competitive
strategy. One day, like operational excellence, rich product
features, everyday low prices, high product quality and
short time-to-market, data quality will be expected by our
markets. In the meantime, each company has the opportunity
to differentiate itself through the quality of its data.
Leading companies are now defining what the marketplace data
quality expectation will be.
Improving the data quality of an organization creates many
benefits such as improved speed to solutions, a “single
version of the truth,” improved customer satisfaction,
improved morale, an enhanced corporate image and consistency
between systems accumulate. And organizations must
selectively choose those benefits to perform further
analysis on and convert to hard dollars. ROI must be
measured on hard dollars.
Data quality improvement is not just another technology to
implement. A program approach to data quality is required to
measure data quality ROI, and organizations must change our
way of doing business to fully exploit data. Investments in
the technologies as well as in organizational changes are
necessary to reap the full rewards. Data quality is right in
the “sweet spot” of modern business objectives that
recognize that whatever business a company is in, it is also
in the business of data. Companies with more data, cleaner
data, accessible data and the means to use that data will
come out ahead.
CSI helps companies differentiate themselves as leaders
through proven data quality services.
Data Quality Program Implementation is a program approach to
data quality for articulating and improving data quality ROI.
Abstracting quality into a set of agreed data rules and
measuring the occurrences of quality violations provides the
measurement in the methodology, which was developed in
conjunction with IT best practice, successful data quality
efforts. Examples of data quality success include targeted
marketing, churn management, market basket analysis,
cross-selling, channel parity, procedure analysis, inventory
tracking, and contact center analysis.
Our Data Audit and Profiling Service helps guide and direct
the planning of any information strategy. In conducting this
service, CSI has discovered a number of issues important to
current production and development projects. Data and table
structures in entire systems – operational and data
warehouse - are navigated to determine the cleanliness in
the main areas of data quality challenges including
referential integrity, uniqueness, cardinality, subtype/supertype
constructs, and domain adherence, conditional data,
derivations, and consistency of data. Data audit and
profiling can be performed with software programs like IQ
Insight from Business Objects or a client’s profiling tool.
For more information:
Download FREE White Paper on Continuous Data Quality
Improvement by Establishing a Data Quality Competency Center
Download FREE White Paper on Strategic Approach to Data
Migration: Performing a Data Quality Initiative Up Front
Reduces Rework and Risk While Improving Speed-to-Market
Download FREE White Paper on Implementing an Integrated
Methodology for Data Profiling and Cleansing
Client Success: CSI's Data Quality Center of Excellence
helps client improve overall data quality, reduce total cost
of ownership, reduce risk with a strategic data migration
and enhances overall decision-making processes
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