As Halloween night quickly approaches, there is only one question on every kid’s mind: how can I maximize my candy haul this year with the best possible candy? This kind of question lends itself perfectly to data science approaches that enable quick and intuitive analysis of data across multiple sources.

Businesses and consumers are getting better at recognizing the direct carbon cost of the products they use. As such, we’re seeing an increased use of sustainable materials in consumer goods and global products. That is a big positive trend, but there’s a bigger picture to explore. Value chains make up 90% of an organization’s environmental impact, according to the Carbon Trust.

There are many good uses of data. With data, we can monitor our business, the overall business, or specific business units. We can segment based on the customer verticals or whether they run in the public or private cloud. We can understand customers better, see usage patterns and main consumption drivers. We can find customer pain points, see where they get stuck, and understand how different bugs affect them.

With the launch of the Cloudera Public Cloud 7.2.12, the Streams Messaging for Data Hub deployments have gotten some interesting new features! From this release, Streams Messaging templates will support scaling with automatic rebalancing allowing you to grow or shrink your Apache Kafka cluster based on demand.

With the latest release of Cloudera DataFlow for the Public Cloud (CDF-PC) we added new CLI capabilities that allow you to automate data flow deployments, making it easier than ever before to incorporate Apache NiFi flow deployments into your CI/CD pipelines. This blog post walks you through the data flow development lifecycle and how you can use APIs in CDP Public Cloud to fully automate your flow deployments.