If someone asked you what makes data “healthy”, what would you say? What IS data health? Healthy data just means data that is quality, accessible, trusted, and secure, right? Wrong. Let's dissect. Data health really has nothing to do with the data itself, if you think about it.

Machine learning (ML), more than any other workflow, has imposed the most stress on modern data architectures. Its success is often contingent on the collaboration of polyglot data teams stitching together SQL- and Python-based pipelines to execute the many steps that take place from data ingestion to ML model inference.

It’s hard to believe enterprise BI platforms have been around for three decades. In that time, they have served the purpose of collecting and analyzing large amounts of data to help businesses make more informed decisions. But in today’s data-driven economy, analysts struggle to keep up with the myriad of business intelligence reports from traditional BI tools – which fail to effectively and efficiently analyze and interpret data in real-time.

If data is currency in today’s digital environment, then organizations should waste no time in making sure every business user has fast access to data-driven insights.

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.