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When is data too clean to be useful for enterprise AI?

CIO Business Intelligence

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Data 352
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Enterprises reevaluate virtualization strategies amid Broadcom uncertainty

Network World

Its enterprise-grade. For enterprises navigating this uncertainly, the challenge isnt just finding a replacement for VMware. It would take a midsize enterprise at least two years to untangle much of its dependency upon VMware, and it could take a large enterprise up to four years. IDC analyst Stephen Elliot concurs.

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Tariff war throws building of data centers into disarray

Network World

Enterprise IT leaders are facing a double-whammy of uncertainties complicating their data center building decisions: The ever-changing realities of genAI strategies, and the back-and-forth nature of the current tariff wars pushed by the United States. And if you slow down AI, that will slow down the data centers.

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Equinix to cut 3% of staff amidst the greatest demand for data center infrastructure ever

Network World

Even as demand for data infrastructure surges to an all-time high, Equinix is planning to lay off 3% of its workforce, suggesting a growing skills mismatch in the industry. According to Goldman Sachs , data center demand in the US alone is projected to nearly triple by 2030, driving more than $1 trillion in investment.

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The Cost-Plus World of Supply Chains: The Macroeconomic and Geopolitical Environment

From new pricing strategies and material substitutability to alternative suppliers and stockpiling, a new GEP-commissioned Economist Impact report reveals that enterprises are adopting a variety of approaches underpinned by data and technology.

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Sustainability, grid demands, AI workloads will challenge data center growth in 2025

Network World

Data centers this year will face several challenges as the demand for artificial intelligence introduces an evolution in AI hardware, on-premises and cloud-based strategies for training and inference, and innovations in power distributionsall while opposition to new data center developments continues to grow.

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Red Hat’s AI portfolio evolves to address enterprise deployment challenges

Network World

Red Hat announced updates to Red Hat OpenShift AI and Red Hat Enterprise Linux AI (RHEL AI), with a goal of addressing the high costs and technical complexity of scaling AI beyond pilot projects into full deployment. IDC predicts that enterprises will spend $227 billion on AI this year, embedding AI capabilities into core business operations.

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Top Considerations for Building an Open Cloud Data Lake

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.

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TCO Considerations of Using a Cloud Data Warehouse for BI and Analytics

Enterprises are pouring money into data management software – to the tune of $73 billion in 2020 – but are seeing very little return on their data investments.

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5 Things a Data Scientist Can Do to Stay Current

Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Collecting and accessing data from outside sources.

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Building Best-in-Class Enterprise Analytics

Speaker: Anthony Roach, Director of Product Management at Tableau Software, and Jeremiah Morrow, Partner Solution Marketing Director at Dremio

Tableau works with Strategic Partners like Dremio to build data integrations that bring the two technologies together, creating a seamless and efficient customer experience. As a result, these two solutions come together to deliver: Lightning-fast BI and interactive analytics directly on data wherever it is stored.

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Partner Webinar: A Framework for Building Data Mesh Architecture

Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri

Data teams in large enterprise organizations are facing greater demand for data to satisfy a wide range of analytic use cases. Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments.

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The Forrester Wave™: AI/ML Platforms: Vendor Strategy, Market Presence, and Capabilities Overview

As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams.

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2021 State of Automatic Speech Recognition Report

Speech is a powerful tool for the enterprise with the ability to unlock insights and automate actions. To answer this question, Deepgram partnered with Opus Research to examine the state of ASR in the enterprise across 400 decision-makers. Where speech data is underutilized.

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Value-Driven AI: Applying Lessons Learned from Predictive AI to Generative

Speaker: Data Robot

Enterprise AI maturity has evolved dramatically over the past 5 years. Most enterprises have now experienced their first successes with predictive AI, but the pace and scale of impact have too often been underwhelming. Now generative AI has emerged and captivated the minds and imaginations of leaders and innovators everywhere.