Today, organizations view data as a valuable asset, the availability of which enables business users to make well-informed and effective business decisions. However, good, information-based decisions are incumbent upon the users’ interpretation and understanding of the analysis or data delivered. And users' understanding of information is a challenge that goes beyond conventional data quality issues. Other challenges include timeliness, reliability and completeness.
Poor user clarity leads to lack of faith on the BI/ analytical reports delivered undermining several million dollars of investment and efforts in developing a robust Enterprise Analytics infrastructure. This calls for a better understanding of how well data is understood by business communities and identifying areas of work and redesign. By constantly monitoring Data Health in a scientific manner, the BI team can identify areas of concern and measure delta improvements in a definitive way. Cognizant's Enterprise Data Clarity (EDC) framework and solution helps customers keep a constant tab on the data pulse of the organization.
Data Themes in EDC
Cognizant's EDC Framework
Our transformational concept, Enterprise Data Clarity (EDC), is a scientific approach towards continuously improving the health of enterprise-wide data. EDC is defined on the basis of multiple data themes. Business teams rate these themes and lead to improved understanding of focus areas for Enterprise Analytics (EA) teams.
Survival
Timeliness
Significance
Uniformity
Is the right set of data available to the user? What are the missing data elements? Is the adequate amount of
historical data available to users?
Sales data beyond 2 years is not in the DW but backed up
on tapes.
Do I receive the data when I need it?
Data latency delays information
availability for a critical decision.
Is my data complete and unique?
Gender information not captured
hampers gender specific targeting
needs.
LegitimacyIs my data valid,
relevant and accurate?
Majority of the mails sent out in an
email campaign return due to invalid
or old addresses.
Is the data consistent and relatable across
my systems or business process
areas?
Call center not updated with payment information and they
keep calling customers for payment reminders.
Measuring EDC
EDC is primarily measured using EDC Maturity Index (EMI) that precisely determines the extent of adherence to EDC maturity levels. EMI is typically calculated and presented in a Fit-For-Function scorecard that highlights the functions'/ business units' ratings across the data themes.
This model stat ist ica l ly aggregates the measurement scores of each of the data themes against each of the business themes (Subject Area, Systems or Business Processes). However, these measurements are point-in-time and allows for continuous measurement to identify and weed-out any ambiguous data.
The EDC tool also provides a Time Series Chart to measure improvements made over time under different business themes and data clarity themes. Even the EMI can be tracked as a time series enabling one to track the effect of the steps taken to improve EDC scores.
For more information please send an e-mail to our global team at or visit our Web site at [email protected]://www.cognizant.com/enterpriseanalytics
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centers to revenue centers. We future-proof visionary businesses by combining in-depth domain expertise with analytics and information management best practices that help clients optimize decisions and results. Enterprise
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