As the digital world grows more complex, organizations find that hybrid data management is the key to unlocking new possibilities. Bringing together diverse data streams and harnessing their full potential is no longer a luxury, but a necessity for staying competitive. The ability to blend proprietary and cloud-based data is helping organizations turn raw information into actionable insights, allowing them to fine-tune their AI capabilities and push the boundaries of what’s possible.

Unified platforms such as Cloudera Inc. help companies streamline data from multiple environments to drive better decision-making and improve AI models, according to Bob Laliberte, principal analyst at theCUBE Research. By integrating proprietary and on-premises data into AI systems, businesses can enhance large language models’ accuracy and effectiveness, enabling more precise and valuable insights. This approach allows organizations to extend AI’s capabilities, especially in industries where accuracy is critical.

the CUBE Research’s Bob Laliberte and co-host Rebecca Knight on the set at Cloudera Evolve24.

“[It’s about] having that hybrid model, having that unified nature of the data where you can bring to bear not only what you’ve attached from the model and the internet, but also what you have on-premises to … drive up the efficacy to provide that crucial context … to make it worthwhile deploying,” Laliberte told theCUBE in an article.

During the Cloudera Evolve24 event, theCUBE Research’s  Bob Laliberte, principal analyst at theCUBE Research, and co-host Rebecca Knight talked with industry executives, customers and partners about effective hybrid data management, integrating AI and fostering innovation. (* Disclosure below.)

Here are three key insights you may have missed from theCUBE’s coverage:

1. Cloudera’s hybrid data management solutions are designed to accelerate AI-driven results.

Cloudera’s hybrid data management approach, designed to meet modern, distributed IT environments’ needs, has made the company a central player in AI-driven data management. By combining on-premises and cloud data management, Cloudera enables organizations to analyze and process data more efficiently — a critical capability as AI’s role in enterprise technology becomes increasingly dominant, according to Bob Laliberte, principal analyst at theCUBE.

“[Cloudera is] trying to represent themselves as the hybrid data management system and recognizing the fact that modern IT environments are highly distributed,” he said during the event. “What we’re seeing is Cloudera coming out and putting together a hybrid solution that enables organizations to get the compute to where the data is and enable organizations to accelerate their insights either from analytics or AI.”

AI has been top-of-mind for the company’s Chief Executive Officer, Charles Sansbury (pictured), chief executive officer of Cloudera, since his appointment last year. He has led the company in its core focus on helping customers accelerate their AI capabilities by operationalizing their data and optimizing its use in AI models.

Charles Sansbury, chief executive officer of Cloudera, talks with theCUBE about Cloudera’s focus on AI.

“Since I’ve joined, AI has become the absolute topic,” Sansbury told theCUBE during the event. “We’ve been doing what used to be called machine learning-based models for customers for 10 years. As compute has gotten faster and access to data has gotten greater, machine learning has evolved into what we call AI today, but it moved to one of our strengths.”

Customer needs have driven Cloudera to focus on rapid returns from AI investments, according to Sansbury. Many businesses want quick wins in their AI deployments, leading Cloudera to prioritize operationalizing AI across public, private and on-premises environments. This comprehensive approach helps organizations maximize the value of their data while minimizing operational complexity.

“I heard every customer talk about the importance of AI and investing aggressively for it,” Sansbury recalled. “And then I heard, ‘But the folks who approve my investment, my board of directors, they want a return quickly … what are the quick wins that we can get in terms of applications or use cases?’”

Cloudera’s focus on optimizing hybrid data management and leveraging AI has made it a key player in helping companies operationalize AI, according to Sansbury. By providing the infrastructure to structure and manage data, Cloudera enables organizations to train and deploy AI models efficiently, enhancing the AI experience for its customers.

“We are not building large language models; that is not what we do,” Sansbury said. “But we are providing the infrastructure and capabilities to make data available and appropriately structured to feed and train models.”

Here’s theCUBE’s complete video interview with Sansbury:

2. Cloudera expands its enterprise AI ecosystem through partnerships to deliver scalable AI solutions.

Cloudera has expanded its enterprise AI ecosystem by partnering with top technology firms to offer customers robust, scalable AI solutions, according to Abhas Ricky, chief strategy officer of Cloudera. Its ecosystem includes collaborations with major players such as Amazon Web Services, Nvidia Corp., Google LLC, Anthropic PBC and Snowflake Inc. Each organization contributes unique capabilities that enhance Cloudera’s data and AI capabilities.

“The idea is AI as a team sport,” Ricky said during the event. “The purpose of the enterprise AI ecosystem is to work together with these ‘crème de la crème’ companies … to make a joint customer successful.”

Cloudera’s partnership with Nvidia is a prime example of its strategy to accelerate AI scalability, according to Priyank Patel, vice president of artificial intelligence and machine learning at Cloudera. By integrating Nvidia NIM microservices, Cloudera’s AI Inference service boosts large language model performance by 36 times, facilitating faster private AI deployments on public cloud and on-premises infrastructures.

Abhas Ricky, chief strategy officer of Cloudera, talks with theCUBE about Cloudera’s growing partnership network and providing true hybrid solutions.

“What we are integrating is the software stack that the Nvidia team has built out, something called NIM,”  Patel told theCUBE during the event. It’s the model serving offering from Cloudera that works anywhere … and fundamentally enables our customers and enterprises to have private endpoints for AI.”

Cloudera’s expansion also includes adding over 150 Google Gemini models from Google Vertex and Snowflake’s querying capabilities through the Cloudera lakehouse, making the ecosystem even more powerful, according to Ricky. These integrations allow companies to bring models directly to the data, reducing the need to move data across different environments.

“We work with Claude Opus or Claude Sonnet 3.4 and a host of others,” he told theCUBE. “Across all of these capabilities, the idea is [that] you want to be able to bring the models to the data and not the data to the models.”

Cloudera’s emphasis on AI-based hybrid data management solutions makes it a unique provider, allowing customers to manage workloads flexibly across private and public clouds without costly application refactoring, according to Ricky. This focus helps businesses achieve AI-driven results faster and more efficiently.

“I generally believe we’re the only provider for true hybrid solutions,” Ricky emphasized. “If you can move your workloads and applications bi-directionally between private cloud and public cloud … that’s what hybrid means, and that’s what we’re focused on.”

Here’s theCUBE’s complete video interview with Patel:

3. Cloudera enables customers and partners to achieve data-driven efficiency and improve performance across industries.

Cloudera’s collaboration with MDClone Ltd. aims to address one of healthcare’s biggest challenges — managing sensitive patient data while providing actionable insights, according to  Luz Erez, chief technology officer of MDClone. The introduction of synthetic data technology allows healthcare providers to work with data that preserves privacy while remaining statistically accurate. This advancement helps remove barriers around Protected Health Information, enabling broader data-sharing possibilities.

“We had to invent or build for ourselves something called synthetic data,” Erez told theCUBE during the event. “Synthetic data, what it’s doing is mixing patients so there is no one-to-one relationship between the original data and the data that you get.”

MDClone’s synthetic data, coupled with Cloudera’s scalable infrastructure, allows healthcare organizations to analyze data on-premises, addressing security concerns while increasing operational efficiency, according to Erez. This solution is especially critical for large institutions such as the National Institute of Health, which handles vast amounts of data.

There would be no MDClone without Cloudera, Erez observed, citing a Log4J security breach. “If we weren’t using Cloudera and we’d build our own stack from scratch, we would have had to go to each one of those components … and then we would have to reinstall for all our clients. We pick up to Cloudera … then, the next morning, we have [an] installation package that we can deploy for our clients.”

Ryan Garnett, senior manager of business solutions at Halifax International Airport Authority, talks with theCUBE about how Halifax Airport harnesses data for predictive insights to enhance the passenger experience.

Similarly, Halifax International Airport leveraged Cloudera’s hybrid data management solutions to improve operational efficiency and the passenger experience,  according to Ryan Garnett, senior manager of business solutions at Halifax International Airport Authority. With Cloudera’s predictive insights, Halifax Airport has reduced costs by 40%, transitioning from manual processes to automated systems that predict passenger volumes and optimize operations.

“We have years of data, and we can classify them,” Garnett told theCUBE during the event. “We use different machine learning algorithms to predict what’s going to happen tomorrow, what’s going to happen in a week or what’s going to happen in a month.”

By integrating various data sources such as weather conditions, traffic and flight delays, Halifax aims to reduce traveler anxiety through real-time updates. These predictive insights help passengers make informed decisions and improve overall travel experiences.

Here’s theCUBE’s complete video interview with Garnett:

To watch more of theCUBE’s coverage of the Cloudera Evolve24 event, here’s our complete event video playlist:

(* Disclosure: TheCUBE is a paid media partner for Cloudera Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE