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The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of datadriven decisions that will drive your business forward.
This approach delivers substantial benefits: consistent execution, lower costs, better security, and systems that can be maintained like traditional software. This translates to higher costs and slower response times. But beneath the surface, its a patchwork of brittle improvisation and runaway costs.
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Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
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CIOs are under increasing pressure to deliver meaningful returns from generative AI initiatives, yet spiraling costs and complex governance challenges are undermining their efforts, according to Gartner. hours per week by integrating generative AI into their workflows, these benefits are not felt equally across the workforce.
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Still, CIOs have reason to drive AI capabilities and employee adoption, as only 16% of companies are reinvention ready with fully modernized data foundations and end-to-end platform integration to support automation across most business processes, according to Accenture. Gen AI holds the potential to facilitate that.
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It also has the benefit that as underlying AI costs drop over time service providers can extract more margin for this work. A third way that AI agents could be priced is by calculating the underlying costs and charging a small markup, he says. Potentially good for customers, but maybe not for shareholder returns.
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Despite all the interest in artificial intelligence (AI) and generative AI (GenAI), ISGs Buyers Guide for Data Platforms serves as a reminder of the ongoing importance of product experience functionality to address adaptability, manageability, reliability and usability. This is especially true for mission-critical workloads.
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In this post, we focus on datamanagement implementation options such as accessing data directly in Amazon Simple Storage Service (Amazon S3), using popular data formats like Parquet, or using open table formats like Iceberg. Datamanagement is the foundation of quantitative research.
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At AWS, we are committed to empowering organizations with tools that streamline data analytics and transformation processes. This integration enables data teams to efficiently transform and managedata using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience.
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