Systems | Development | Analytics | API | Testing

One of my favorite analogies is that data is the lifeblood of the business. Before you roll your eyes at me (I see it now), hear me out. At your annual physical, when you get your blood work done, think of how much information is uncovered about your overall health from a tiny vial of your blood. From those 10 CCs they extract comes back pages of information regarding your cell counts, glucose, cholesterol, and other information.

Generative AI is a powerful tool for accelerating the branding process for new products or compounds.

Artificial intelligence (AI) has led to a seismic shift in the business landscape, largely due to the surge in popularity of large language models like ChatGPT. From predictive models that foster better decision-making to generative AI code tools that enable teams to build applications faster, AI offers incredible benefits to organizations. Businesses need to embrace this technology or risk falling behind their competitors.

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.

Recently, I got my hands dirty working with Apache Flink®. The experience was a little overwhelming. I have spent years working with streaming technologies but Flink was new to me and the resources online were rarely what I needed. Thankfully, I had access to some of the best Flink experts in the business to provide me with first-class advice, but not everyone has access to an expert when they need one.

Data is essential to marketing. It’s how we know our audience and measure campaign outcomes. It shows us where to adjust a campaign on the fly, for even better results. But working with data is increasingly complex, and having the right stack of technologies is invaluable.

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.