Three Steps to Data Quality in the Cloud

It’s time for providers of market intelligence and databases to make a formal commitment to their clients that every one of their data points is current and as accurate as possible.

Joe Kornik | July 16, 2013

Three Steps to Data Quality in the Cloud By Ruth McHenry

It's time for providers of market intelligence and databases to make a formal commitment to their clients that every one of their data points is current and as accurate as possible.

Our company recently launched a corporate-wide quality initiative to optimize reliability and usability of our cloud-based solutions. In working on this year-long project, we identified three key areas that must be addressed to ensure the reliability and usability of data, reports, and analysis for investment and biopharmaceutical decision-making:

  1. Data Integrity: Underlying internal and external data sources must be current and accurate to create reliable reports and up-to-date analysis.
  2. Consistency: Results and recommendations from diverse searches should reach uniform conclusions and be presented in a familiar manner for a seamless user experience.
  3. Accessibility: Streamlined and intuitive interfaces need constant refinement to reduce the number of clicks between a customer's inquiry and an actionable result.

As the big data requirements of global industries mature, it's not enough to simply provide data. We have to stay ahead of the curve by innovating with services, features and analysis that deliver practical answers based on trustworthy data.

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