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Capitalizing on Efficiency — Shifting Investment from Data Platforms to Generative AI Initiatives…
- Organizations are increasingly looking towards generative artificial intelligence (AI) as the next frontier for innovation and advantage.
- Optimizing existing data platforms is an impactful strategy to facilitate this transition.
- Optimizing and streamlining existing data platforms boosts efficiency and also liberates capital that can be redirected towards pioneering AI projects.
- Streamlining operations, minimizing waste and ensuring that data platforms operate at peak efficiency is crucial to unleashing the full potential of generative AI.
- Minimizing waste involves critical assessment and overhaul of existing data management practices, including cumbersome ETL/ELT, and data engineering processes.
- Companies that optimized their ETL/ELT processes saw a reduction in data processing costs by up to 30%, freeing up resources for other initiatives.
- The focus should be on breaking through complexity by democratizing data access through a single language and providing elements to future-proof the architecture for new capabilities.
- Two key changes to the traditional approach are shifting capital from data management to AI innovation and adopting an agile stepwise approach.
- By optimizing data platforms and adopting decentralized models, organizations can move capital towards cutting-edge generative AI initiatives, transforming their data from a static asset into a dynamic catalyst for innovation.
- Investing in AI is the way to gain a competitive edge and future proof the company, it's not just about having a big idea but also efficiently allocating resources to count.
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