Analytics

Fivetran's new offering simplifies data lake table maintenance, delivering optimized, query-ready data that is always in sync.

Apps are the way to democratize AI: to make it accessible to everyone and streamline customers’ experiences with faster time to insights. According to a recent IDC survey, AI applications is currently the largest category of AI software, accounting for roughly one-half of the market’s overall revenue in 2023.

In today’s world, innovation doesn’t happen in a vacuum; collaboration can help technological breakthroughs happen faster. The rise of AI, for example, will depend on the collaboration between data and development. We’re increasingly seeing software engineering workloads that are deeply intertwined with a strong data foundation.

Businesses that are best able to leverage data have a significant competitive advantage. This is especially true in financial services, an industry in which leading organizations are in constant competition to develop the most responsive, personalized customer experiences. Often, however, legacy infrastructure, data silos, and batch systems introduce significant technical hurdles.

A database is a storage system that stores data in an organized manner for easy access and management. In just the last two years, 90% of the world’s data has been created, and the volume of global data doubles every two years. All this data is stored in databases. So, whether you’re checking the weather on your phone, making an online purchase, or even reading this blog, you’re accessing data stored in a database, highlighting their importance in modern data management.

The complexity and variability of project-based businesses represent distinct challenges for finance and accounting teams. Costing, procurement, subcontractor management, and labor combine to create a level of intricacy that businesses in other sectors don’t have to contend with. How do you navigate the complexity of your project-based financial reporting?

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.

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.

Originally created in the 1890s, the Swiss army knife was a logical solution to officers’ need to be able to repair their weapons, open their canned food, and cut things as needed. Since then, simple items that offer multiple solutions to achieve a goal are often referred to as being the Swiss army knife of their kind.

Open source file and table formats have garnered much interest in the data industry because of their potential for interoperability — unlocking the ability for many technologies to safely operate over a single copy of data. Greater interoperability not only reduces the complexity and costs associated with using many tools and processing engines in parallel, but it would also reduce potential risks associated with vendor lock-in.