From adaptive AI systems to data fabrics, Gartner_IT shares the 12 trends that data and analytics leaders need to build on to drive new growth, resilience and innovation 💡 Check them out here: GartnerDA Data Analytics
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to achieve value from D&A at scale. Manage AI risk and enact connected governance across distributed systems, edge environments and emerging ecosystems.We've identified the data and analytics trends that represent business, market and technology dynamics that you cannot afford to ignore. These trends also help prioritize investments to drive new growth, efficiency, resilience and innovation.As decisions become more connected, contextual and continuous, it's increasingly important to.
However, to build and manage adaptive AI systems, adopt AI engineering practices. AI engineering orchestrates and optimizes applications to adapt to, resist or absorb disruptions, facilitating the management of adaptive systems.Many organizations attempt to tackle AI without considering AI-specific data management issues. “Without the right data, building AI is risky and possibly dangerous,” says Sallam. As such, it is critical to formalize data-centric AI and AI-centric data.
As an example, the city of Turku in Finland foundgaps in its data held back its innovation. By integrating fragmented data assets, it was able to reuse data, reduce time to market by two-thirds and create a
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