At a distance of a million miles from Earth, the James Webb Space Telescope is pushing the edge of data transfer capabilities. The observatory launched Dec. 25 2021 on a mission to look at the early universe, at exoplanets, and at other objects of celestial interest. But first it must pass a rigorous, months-long commissioning period to make sure that the data will get back to Earth properly. Mission managers provided an update Feb.
We’re entering the defining decade of data. While every aspect of our lives have been changed by data in recent years, the next ten will see data rebuild the world around us. Every business, in every industry, needs a plan to adapt to this new world if they want to thrive. But how? That’s a question in the minds of data leaders, CEOs, and board members. The right approach is critical if companies want to dominate this new era. The wrong decision can spell disaster.
Data infrastructure is rapidly growing and evolving along with infrastructure for AI/ML, with the latter growing largely independent from the former. An emerging generation of AI/ML tooling emphasizes data-centric versus model-centric approaches to the ML development lifecycle. These tools recognize that data is the foundation for AI and seek to open opportunities for all data professionals to participate by eliminating the unnecessary complexity of traditional model-centric solutions.
Gaining an accurate view of revenue intelligence for B2B markers is challenging. With disconnected and dirty data residing in many systems, customers need a solution that collects, normalizes, and aggregates information into reports that answer the questions B2B marketers should have a handle on. And let’s face it, no matter how great a set of standard reports might be, every customer wants to see their data a little differently.
