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Bringing More AI to Snowflake, the Data Cloud

DataRobot Blog

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. Exploratory Data Analysis After we connect to Snowflake, we can start our ML experiment.

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DS Smith sets a single-cloud agenda for sustainability

CIO Business Intelligence

Much of our digital agenda is around data. Its digital transformation began with an application modernization phase, in which Dickson and her IT teams determined which applications should be hosted in the public cloud and which should remain on a private cloud. Before we were quite fragmented across different technologies.

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Rapid AI Iteration, Reducing Cycle Time: Key Learnings from the Big Data & AI World Asia Conference

DataRobot Blog

Organizations are looking to deliver more business value from their AI investments, a hot topic at Big Data & AI World Asia. At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. Automate with Rapid Iteration to Get to Scale and Compliance.

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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications. The impact of these investments will become evident in the coming years.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

After all, 41% of employees acquire, modify, or create technology outside of IT’s visibility , and 52% of respondents to EY’s Global Third-Party Risk Management Survey had an outage — and 38% reported a data breach — caused by third parties over the past two years. There may be times when department-specific data needs and tools are required.

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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. AI products are automated systems that collect and learn from data to make user-facing decisions. Why AI software development is different.

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ConocoPhillips enlists 3D printing for supply efficiencies on Alaska’s North Slope

CIO Business Intelligence

Reining in the rugged and remote Through rapid cycles of discovery and experimentation, Mathur and De Bernardi’s cross-functional team devised a solution that leaned heavily on additive manufacturing, more commonly known as “3D printing.” Mathur says the data-driven nature of the solution will in time strengthen the capability.