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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. In either case, the change can affect analytics.
Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement. Indeed, IDC has predicted that by the end of 2024, 65% of CIOs will face pressure to adopt digital tech , such as generative AI and deep analytics.
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.
Currently, many businesses are using public clouds to do their Data Management. Data Management platforms (DMPs) started becoming popular during the late 1990s and the early 2000s. Click to learn more about author Keith D.
Advanced analytics and AI/ML continue to be hot data trends in 2023. According to a recent IDC study, “executives openly articulate the need for their organizations to be more data-driven, to be ‘data companies,’ and to increase their enterprise intelligence.”
Key Takeaways Data Mesh is a modern data management architectural strategy that decentralizes development of trusted data products to support real-time business decisions and analytics. It’s time to rethink how you manage data to democratize it and make it more accessible. What is Data Mesh?
But with data integrity, you gain more trustworthy and dependable AI results for confident data-driven decisions that help you grow the business, move quickly, reduce costs, and manage risk and compliance. Mainframe and IBM i systems remain critical parts of the modern data center and are vital to the success of these data initiatives.
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