In a data-driven world, financial services organizations are racing to harness the transformative power of AI. However, this journey is not without challenges. We know AI has a data problem. Without the right data in the right place, even the most sophisticated AI strategies fall short. IT leaders in the financial services sector understand that…
The data storage landscape is undergoing a transformational change. AI is changing how systems need to handle both large amounts of data and the speed at which that data can be processed. Where enterprise organizations once depended on traditional SAN/NAS architectures, the explosive growth of unstructured data, now measured in petabytes, has made one thing…
The success of enterprise AI is closely tied to the quality and accuracy of the data it uses to train its models. This has been underscored by numerous reports that underscore the critical role of data quality. Historically, enterprises worked primarily with structured data, which is clean, well-organized, and easily analyzed. This includes data such…
As artificial intelligence (AI) technologies and automation evolve, the way we work is changing faster than ever. Traditional jobs are being redefined, and our growing dependence on technology is altering how we tackle tasks in many industries. Alongside the challenges of an aging population, these shifts are creating a significant transformation in the U.S. workforce….
Cloudera, a hybrid platform for data, analytics, and AI, has announced an integration with Snowflake, an AI-powered cloud data platform, aimed at providing enterprises with an open and unified hybrid data lakehouse. At the heart of this new lakehouse is Iceberg REST Catalog which leverages Apache Iceberg, an open table format designed for large-scale data…
Finding data to train AI models has become a major headache for enterprises, as they have largely exhausted the most useful publicly available datasets. While organizations possess valuable proprietary data that could enhance their AI training efforts, they are often hesitant to leverage it due to privacy concerns, compliance issues, and the costs associated with…
In today’s dynamic technological landscape, organizations are racing to leverage the power of GenAI to gain a competitive edge, underscoring the critical need for efficient integration of these solutions into their operations. However, as organizations strive to implement these transformative technologies, they often encounter challenges such as managing escalating costs, maintaining quality standards, and mitigating…
In today’s dynamic technological landscape, organizations are racing to leverage the power of GenAI to gain a competitive edge, underscoring the critical need for efficient integration of these solutions into their operations. However, as organizations strive to implement these transformative technologies, they often encounter challenges such as managing escalating costs, maintaining quality standards, and mitigating…
When “The Social Dilemma” documentary came out in 2020, consumers called for a mass exodus from social media and the end of user data capture. While opening the public’s eyes to the inner workings of social media was important, it failed to show the benefits of online personalization that wouldn’t be possible without data collection….
Organizations are struggling to find ways to deliver GenAI successfully. The key challenges to GenAI deployment include difficulty in integrating GenAI solutions with the existing tech stack and customizing the LLMs to meet the requirements of internal operations. Oracle, one of the world’s premier enterprise software and cloud solutions companies, might have just found a…
