Analytics

In today’s dynamic business landscape, numerous organizations are transitioning to the Snowflake Data Cloud, seeking more agile, secure and efficient solutions to manage and activate customer data. Yet, the timelines and engineering resources needed to support implementation haven’t always kept pace with the increased market demand, impeding innovation.

As data leaders embark on their data strategy in the new year, data centralization is integral to demonstrate value.

There are a lot of self-service data platforms out there. And picking the one that best fits your organization’s needs can be challenging. In this article, we’ll discuss what you should expect from a self-service data platform and what features make it a good choice.

As your organization grows, so does the complexity of managing data. It’s a critical challenge—get it wrong, and you’re facing a world of siloed and inaccurate data, compliance nightmares, and security risks. The consequences of poor data governance are not just operational hiccups; they can directly impact an organization’s performance. If you’re looking for a solution to tackle these challenges head-on, you’re in the right place.

As an industry built on data, financial services has always been an early adopter of AI technologies. In a recent industry survey, 46% of respondents said AI has improved customer experience, 35% said it has created operational efficiencies, and 20% said it has reduced total cost of ownership. Now, generative AI (gen AI) has supercharged its importance and organizations have begun heavily investing in this technology.

Vertex AI transcription models in BigQuery let you transcribe speech files and combine them with structured data to build analytics and AI use cases.