In recent years, machine learning operations (MLOps) have become the standard practice for developing, deploying, and managing machine learning models. MLOps standardizes processes and workflows for faster, scalable, and risk-free model deployment, centralizing model management, automating CI/CD for deployment, providing continuous monitoring, and ensuring governance and release best practices.

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

We are thrilled to announce the general availability of the Cloudera AI Inference service, powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise platform, to accelerate generative AI deployments for enterprises. This service supports a range of optimized AI models, enabling seamless and scalable AI inference.

The journey from a great idea for a Generative AI use case to deploying it in a production environment often resembles navigating a maze. Every turn presents new challenges—whether it’s technical hurdles, security concerns, or shifting priorities—that can stall progress or even force you to start over.

According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making. More and more enterprises are leveraging pre-trained models for various applications, from natural language processing to computer vision. For that reason, Cloudera is evaluating a new line of business: Cloudera Integrated Data and AI Exchange (InDaiX).

Imagine a world where your sensitive data moves effortlessly between clouds – secure, private, and far from the prying eyes of the public internet. Today, we’re making that world a reality with the launch of Cloudera Private Link Network. Organizations are continuously seeking ways to enhance their data security. One of the challenges is ensuring that data remains protected as it traverses different cloud environments.

A prominent global bank was thrust into the spotlight for all the wrong reasons. The institution was hit with a staggering fine – multiple billions – for failing to comply with new data protection regulations that ultimately led to a customer data breach. The breach, which exposed sensitive information, not only resulted in financial penalties but also caused significant reputational damage.

Without a doubt, Artificial Intelligence (AI) is revolutionizing businesses, with Australia’s AI spending expected to hit $6.4 billion by 2026. However, according to The State of Enterprise AI and Modern Data Architecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits. In fact, over 25% of respondents stated they don’t have the data infrastructure required to effectively power AI.

It’s nearing the end of the summer in North America, and one report has been a staple on my reading list for more than a decade: the Flexera State of the Cloud Report. The annual survey of hundreds of global IT decision makers assesses cloud strategies, migration trends, and important considerations for companies moving to the cloud or managing cloud environments.

The CRN Tech Innovator Awards spotlight innovative products and services across 36 categories, with winners chosen by CRN staff from over 320 product applications. This year, we’re excited to share that Cloudera’s Open Data Lakehouse 7.1.9 release was named a finalist under the category of Business Intelligence and Data Analytics.