Organizations increasingly rely on streaming data sources not only to bring data into the enterprise but also to perform streaming analytics that accelerate the process of being able to get value from the data early in its lifecycle. As lakehouse architectures (including offerings from Cloudera and IBM) become the norm for data processing and building AI applications, a robust streaming service becomes a critical building block for modern data architectures.

Perhaps your C-suite is already a bit crowded. The typical hierarchy will include a CEO, COO, CFO, CTO, CMO, CIO, and a few more. Adding another position may not be terribly appealing, but there is one C-suite role every company should consider—chief data and analytics officer (CDO or CDAO).

The world is awash with data, no more so than in the telecommunications (telco) industry. With some Cloudera customers ingesting multiple petabytes of data every single day— that’s multiple thousands of terabytes!—there is the potential to understand, in great detail, how people, businesses, cities and ecosystems function.

In the age of the AI revolution, where chatbots, generative AI, and large language models (LLMs) are taking the business world by storm, enterprises are fast realizing the need for strong data control and privacy to protect their confidential and commercially sensitive data, while still providing access to this data for context-specific AI insights.

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But in highly regulated industries where these technologies may be prohibited, the focus is less on off the shelf generative AI, and more on the relationship between their data and how AI can transform their business.

At Cloudera, we’re known for making innovative technological solutions that drive change and impact the world. Our mission is to make data and analytics easy and accessible to everyone. And that doesn’t end with our customer base. We also aim to provide equitable access to career opportunities within data and analytics to the workforce of tomorrow.

The release of ChatGPT pushed the interest in and expectations of Large Language Model based use cases to record heights. Every company is looking to experiment, qualify and eventually release LLM based services to improve their internal operations and to level up their interactions with their users and customers. At Cloudera, we have been working with our customers to help them benefit from this new wave of innovation.

Machine Learning (ML) is at the heart of the boom in AI Applications, revolutionizing various domains. From powering intelligent Large Language Model (LLM) based chatbots like ChatGPT and Bard, to enabling text-to-AI image generators like Stable Diffusion, ML continues to drive innovation. Its transformative impact advances multiple fields from genetics to medicine to finance. Without exaggeration, ML has the potential to profoundly change lives, if it hasn’t already.

The snapshots feature of the Apache Hadoop Distributed Filesystem (HDFS) enables you to capture point-in-time copies of the file system and protect your important data against corruption, user-, or application errors. This feature is available in all versions of Cloudera Data Platform (CDP), Cloudera Distribution for Hadoop (CDH) and Hortonworks Data Platform (HDP).

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).