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Acquisition of Verta's Operational AI Platform Will Transform Cloudera's AI Vision to Reality

In an era where artificial intelligence (AI) is reshaping enterprises across the globe—be it in healthcare, finance, or manufacturing—it’s hard to overstate the transformation that AI has had on businesses, regardless of industry or size. At Cloudera, we recognize the urgent need for bold steps to harness this potential and dramatically accelerate the time to value for AI applications.

Cloudera Introduces AI Inference Service With NVIDIA NIM

We are excited to announce a tech preview of Cloudera AI Inference service powered by the full-stack NVIDIA accelerated computing platform, which includes NVIDIA NIM inference microservices, part of the NVIDIA AI Enterprise software platform for generative AI. Cloudera’s AI Inference service uniquely streamlines the deployment and management of large-scale AI models, delivering high performance and efficiency while maintaining strict privacy and security standards.

Bringing Financial Services Business Use Cases to Life: Leveraging Data Analytics, ML/AI, and Gen AI

The financial services industry is undergoing a significant transformation, driven by the need for data-driven insights, digital transformation, and compliance with evolving regulations. In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation.

Unify your data: AI and Analytics in an Open Lakehouse

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses. Nearly two years ago, Cloudera announced the general availability of Apache Iceberg in the Cloudera platform, which helps users avoid vendor lock-in and implement an open lakehouse. With an open data lakehouse powered by Apache Iceberg, businesses can better tap into the power of analytics and AI.

Retail Media's Business Case for Data Clean Rooms Part 2: Commercial Models

In Part 1 of “Retail Media’s Business Case for Data Clean Rooms,” we discussed how to (1) assess your data assets and (2) define your data structures and permissions. Once you have a plan on paper, you can begin sizing the data clean room opportunity for your business.

Laying the Foundation for Modern Data Architecture

Behind every business decision, there’s underlying data that informs business leaders’ actions. As the market landscape across verticals from financial services to healthcare and manufacturing grows increasingly competitive, those decisions need to happen ever faster and to make them, businesses need to rely on data to reveal insights quickly, as near-real-time as possible.

What is a KPI Dashboard? 6 Key Benefits & Best Practice Examples

From business-wide objectives to long-term targets, every organization has specific metrics they need to track. One way to communicate those insights is a KPI dashboard. Key performance indicator (KPI) dashboards are a great way for executives to improve their management of strategic goals, and keep on top of changes, issues and trends in performance at a high-level, with many useful applications when used correctly, alongside other modern analytics tools.

Retail Media's Business Case for Data Clean Rooms Part 1: Your Data Assets and Permissions

It’s hard to have a conversation in adtech today without hearing the words, “retail media.” The retail media wave is in full force, piquing the interest of any company with a strong, first-party relationship with consumers. Companies are now understanding the value of their data and how that data can power a new, high-margin media business. The two-sided network that exists between retailers and their brands turns into a flywheel for growth.