On August 18, we completed our Enterprise Data Cloud vision of bringing a truly hybrid cloud experience with the general availability of Cloudera Data Platform Private Cloud (CDP Private Cloud). CDP Private Cloud, which is based on Kubernetes (RedHat OpenShift), extends cloud-native speed, simplicity and economics for the connected data lifecycle to the on-prem world, enabling IT to respond to business needs faster and deliver rock-solid service levels so people can be more productive with data.

Live data-streaming offers businesses exciting new opportunities to transform the way they operate, leveraging real-time insights to drive better decision making and enhance operational efficiency. To find out more about how live-streaming data might impact the financial services sector, I sat down for a chat with Dinesh Chandrasekhar, Head of Product Marketing in Cloudera’s data-in-motion Business Unit. If you missed Part 1 of our Q&A, you can catch-up on it here.

Today, we announced the acquisition of the assets and IP of Knarr Analytics, an innovative start-up that provides real-time collaboration, sophisticated data exploration and insight capture capabilities, to complement Qlik’s cloud data and analytics platform.

Evaluating anomalies and unpredicted events like pandemics and ESG concerns In part II of the series, we sat down for an interview with Dr. Richard Harmon, Managing Director of Financial Services at Cloudera, to find out more about how the industry is adopting new technology. You can catch-up and read part 1 of the series, here. Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon.

With only about 35% of machine learning models making into production in the enterprise (IDC), it’s no wonder that production machine learning has become one of the most important focus areas for data scientists and ML engineers alike. As you may remember, we recently announced a full set of MLOps capabilities in Cloudera Machine Learning, our cloud native machine learning tool for the cloud.

In the last blog with Deloitte’s Marc Beierschoder, we talked about what the hybrid cloud is, why it can benefit a business and what the key blockers often are in implementation. You can read it here.

Modern businesses face a continuously growing mountain of data, made up of many different operational processes and performance metrics, which your users need to decipher for insights and proactively monitor in order to ensure business goals are met. Embedded dashboards are one way for your users to keep track of key information while using your application.

Back in 1977, an English mod/rock band called The Jam released a track called “The Modern World.” The same year also saw the dawn of the home computer, with the Apple II and Commodore PET 2001 going on sale at a time when the mainframe was going strong. Fast forward to 2020, and, despite many false claims of its death, the mainframe remains strong; however, to get the most value of from the data inside, mainframe modernization is key.

It’s no secret that today’s data environment is chaotic. Organizations everywhere have to deal with more sources of data, more data types, and more use cases for that data, in order to make mission-critical decisions with confidence.

The Corner Office is pressing their direct reports across the company to “Move To The Cloud” to increase agility and reduce costs. And next to those legacy ERP, HCM, SCM and CRM systems, that mysterious elephant in the room – that “Big Data” platform running in the data center that is driving much of the company’s analytics and BI – looks like a great potential candidate.