BigQuery, PubSub, Scheduler, Monitoring and more work together to make your DevOps processes easier with sampling data.

When it comes to geospatial data, BigQuery can help you store and analyze it, while Tableau can provide powerful visualization capabilities.

There's no denying that OpenAI's remarkable artificial intelligence applications (ChatGPT and DALL-E) have captured the zeitgeist and hurled the topic of Generative AI into every company boardroom. Conversations range from apocalyptic hand-wringing to blissful ignorance. I wonder if ChatGPT will single-handedly save the chatbot industry, or is this just another tech fad that will quickly wither and die?

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.

From electronic medical records and monitoring devices, to personalized medicine and real-time decision-making, data is critical at every turn within modern healthcare. However, the sheer volume and complexity of healthcare data is posing increasing challenges on medical centers and professionals.

In today’s rapidly evolving digital landscape, businesses face numerous challenges when it comes to data management and protection. Defining effective backup, disaster recovery (DR), and business continuity objectives in particular, stand out as crucial. At Hitachi Vantara, we understand the importance of ensuring data resilience and uninterrupted operations for businesses that have embraced or are considering cloud or hybrid-cloud architectures.