hitachi vantara

How AI Inference Is Reshaping Enterprise Infrastructure

Jun 30, 2026 By Sunitha Rao and Nick Loy In Hitachi Vantara
Data center teams are skilled at solving familiar problems such as storage outages, missed forecasts, and late refresh cycles. These are known quantities. Teams have playbooks for them. But 2026 has brought a different kind of pressure. After years of enterprise AI investment concentrated almost entirely on model training, the industry has crossed a threshold: the workload that now defines AI infrastructure isn’t building models. It’s running them. Continuously. At scale. Every day.
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ThoughtSpot June Release: Customize Your Agent

Jun 30, 2026 By ThoughtSpot In ThoughtSpot
Check out what’s new in ThoughtSpot’s latest release! SpotterModel gets smarter: Build complex data models with AI formula suggestions and instant version rollbacks if you make a mistake. No stress, no lost work. Spotter Instructions: Fully customize Spotter’s persona, formatting rules, and strict guardrails. It says exactly what you want it to say—and nothing it shouldn't. Ad Hoc Analysis: Drop local files directly into Spotter for instant answers, or blend them safely with your governed enterprise data.
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astera

Foundation First: Why Model-Agnostic Data Platforms Win

Jun 30, 2026 By Hira Asif In Astera
In 2024, two of the largest data platform companies, each with billions in revenue and dedicated AI research teams, invested in building their own foundation models. One spent roughly $10 million training a 132-billion parameter model on 3,072 NVIDIA H100 GPUs. The other released a 480-billion parameter model optimized for enterprise tasks like SQL generation and code. Both achieved strong results within their compute class.
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confluent

Stream Governance: Making Compliance a Property of Data in Motion

Jun 29, 2026 By Saurabh Ghelani In Confluent
As organizations have transitioned from batch processing to real-time streaming architectures, a critical governance gap has emerged. Legacy data governance tools designed for databases, warehouses, and file systems assume that information is stationary and focus on protecting, classifying, and auditing data at rest.
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confluent

Building Secure, Resilient, and Compliant Fraud Detection With Confluent Cloud

Jun 29, 2026 By Saurabh Ghelani In Confluent
Banking customers expect financial transactions to be completed quickly. Fraud analysis must execute in milliseconds, so traditional batch processing systems are inherently too slow. To safeguard transactions, institutions must shift to proactive, in-flight prevention. Confluent enables this shift by using Apache Kafka and Apache Flink to continuously correlate transactional and behavioral signals, blocking malicious activity before a transaction settles.
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thoughtspot

How to Architect a Clean Context Layer for Trustworthy AI

Jun 29, 2026 By Sonny Rivera In ThoughtSpot
A CFO asks her AI agent a simple question: "What was our ARR at the end of Q3?" The agent finds the subscriptions table, spots a column called arr, sums it up, and returns $16.4M. Strong quarter. Everyone nods. The real number was $13.9M, but no one in the room knew it yet. I hear some version of this story from nearly every data leader I talk to right now, and it almost always starts the same way. They stand up an AI pilot. It looks sharp in the POC.
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