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The death of DIY: How building data pipelines decelerates your data team Traditionally, organizations constructed their own data pipelines, which proved effective in an era with fewer data sources. However, in today’s data-rich landscape, an average organization aggregates data from over 400 sources. Scaling with do-it-yourself (DIY) pipelines poses a significant challenge. While DIY pipelines…

A CIO’s guide to data lake management for GenAI Data lakes are essential for AI because they support diverse data types, offer scalable storage and processing and preserve data in its raw format, providing a robust foundation for training advanced AI and ML models. This ebook provides CIOs with strategies to accelerate and ensure the…

MIT report: AI readiness for C-suite leaders 82% of C-suite leaders say a top priority for their organization in 2024 is scaling AI or generative AI use cases to create business value. This exclusive report by MIT Technology Review Insights, sponsored by Fivetran, explores how enterprise technology and business leaders are preparing their organizations for…

Data Readiness for SAP Applications- Capitalizing on AI, and GenAi to drive Enterprise Forward Data Readiness encompasses an organization’s processes and strategies to ensure their data assets are accurate, accessible, and actionable for AI-driven applications. Data readiness illustrates the transformative impact on operational efficiency, customer experience, and innovation when underpinned by a robust Data Readiness…