Systems | Development | Analytics | API | Testing

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. But, we also know that experimentation alone doesn’t yield business value. Organizations need to usher their ML models out of the lab (i.e., the proof-of-concept phase) and into deployment, which is otherwise known as being “in production”.

It’s no secret that Data Scientists have a difficult job. It feels like a lifetime ago that everyone was talking about data science as the sexiest job of the 21st century. Heck, it was so long ago that people were still meeting in person! Today, the sexy is starting to lose its shine. There’s recognition that it’s nearly impossible to find the unicorn data scientist that was the apple of every CEO’s eye in 2012.

With the general availability of Cloudera DataFlow for the Public Cloud (CDF-PC), our customers can now self-serve deployments of Apache NiFi data flows on Kubernetes clusters in a cost effective way providing auto scaling, resource isolation and monitoring with KPI-based alerting. You can find more information in this release announcement blog post and in this technical deep dive blog post. Any customer willing to run NiFi flows efficiently at scale should now consider adopting CDF-PC.

The word “data” is ubiquitous in narratives of the modern world. And data, the thing itself, is vital to the functioning of that world. This blog discusses quantifications, types, and implications of data. If you’ve ever wondered how much data there is in the world, what types there are and what that means for AI and businesses, then keep reading!

Arjun (my son) sat next to me at my desk. He was a bit nervous but we had practiced 3 times before he was ‘on stage’ in front of hundreds of people and the zoom meeting turned to him. My ten year old began to demonstrate how to deploy an Operational Database in AWS, showcasing how auto-scaling worked and how to set up replication. All of the sales team and my colleagues were quite impressed with him, and I am very proud of him.

Cloudera Data Platform (CDP) brings many improvements to customers by merging technologies from the two legacy platforms, Cloudera Enterprise Data Hub (CDH) and Hortonworks Data Platform (HDP). CDP includes new functionalities as well as superior alternatives to some previously existing functionalities in security and governance. One such major change for CDH users is the replacement of Sentry with Ranger for authorization and access control.

SANTA CLARA, Calif., Nov. 9, 2021 – Cloudera, the enterprise data cloud company, today announced Cloudera Data Platform capabilities available to help federal agencies meet requirements of the Biden Administration’s Executive Order on improving the Nation’s cybersecurity. Cloudera is committed to supporting the federal government in adhering to this executive order with the company’s technology and special government rates.

Guest Author Roozbeh Aliabadi is CEO at ReadyAI Our children have the right to be AI-educated so they can thrive intellectually, emotionally, and morally alongside AI. In the next decade or so, for most children, AI will be their co-workers, drivers, insurance agents, customer service reps, bank tellers, receptionists, radiologists, in short, a natural part of their lives.

Have you ever asked a data scientist if they wanted their code to run faster? You would probably get a more varied response asking if the earth is flat. It really isn’t any different from anything else in tech, faster is almost always better. One of the best ways to make a substantial improvement in processing time is to, if you haven’t already, switched from CPUs to GPUs.

Becoming a data-driven organization is not exactly getting any easier. Businesses are flooded with ever more data. Although it is true that more data enables more insight, the effort needed to separate the wheat from the chaff grows exponentially. Doing so and truly understanding the data is more important than ever, especially when data privacy regulations are tightening.