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You want to rely on data integrity to ensure you avoid simple mistakes because of poor sourcing or data that may not be correctly organized and verified. The post DataObservability and Its Impact on the Data Operations Lifecycle appeared first on DATAVERSITY. That requires the […].
Author’s note: this article about dataobservability and its role in building trusted data has been adapted from an article originally published in Enterprise Management 360. Is your data ready to use? That’s what makes this a critical element of a robust data integrity strategy. What is DataObservability?
It includes streaming data from smart devices and IoT sensors, mobile trace data, and more. Data is the fuel that feeds digital transformation. But with all that data, there are new challenges that may prompt you to rethink your dataobservability strategy. Learn more here.
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Video of the Week: Beyond Monitoring: The Rise of DataObservability Watch as Monte Carlo’s Shane Murray introduces “DataObservability” as the game-changing solution to the costly reality of broken data in advanced data teams.
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With the responsibility to build data products at the domain level, data governance must be federated or implemented at the domain level for greater autonomy, yet coordinated with a centralized data governance strategy. Standardizing naming conventions also makes data products interoperable.
For instance, a data breach or violation of privacy standards can lead to liability, expensive fines, and a slew of negative publicity that’s a hit to brand reputation and trustworthiness. Going into 2024, we see a continued trend towards enabling democratized delivery of data across business functions with repeatable, scalable processes.
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