We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.
Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Due to the lack of tooling specifically designed for data discovery, exploration, and preliminary analysis, this presents a significant challenge for these teams.
Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. Over the last few years, we have had a front-row seat in our customers’ hybrid cloud journey as they expand their data estate across the edge, on-premise, and multiple cloud providers.
At Cloudera we’re building the world’s only hybrid data platform that’s founded on open source and truly hybrid. What do we mean by truly hybrid? Well, not only does it seamlessly support on-premises and cloud-based deployments alike, but uniquely, it is cloud vendor agnostic, allowing multi-cloud strategies to thrive.
Deciding to adopt an AI-first strategy is the easy part. Figuring out how to implement it takes a little more effort. It requires a clear-eyed vision built around well-defined goals and a realistic execution plan. Being AI-first means setting up your organization for the future. By leveraging data, analytics, and automation, a company can gain a better understanding of where it is and where it needs to go.
