As a modern data leader, you know that real-time access to data-driven insights is key to driving higher levels of business growth and innovation, and better customer experiences. You also know that when frontline employees have easier access to data they’re able to make better decisions that ultimately boost your bottom line. But what happens when employees don’t trust the data in front of them?

In 2020, the pandemic tested supply chains in a manner few have seen in our lifetimes, with businesses like Apple struggling to predict demand and keep factory lines moving. The weaknesses exposed by this crisis are not brand new, but they should be a wake-up call that current strategies are not sustainable. The limitations of modern supply chains were becoming apparent last year when companies struggled to react to new tariffs and restrictions caused by Brexit and the U.S.-China trade war.

If you’ve followed Cloudera for a while, you know we’ve long been singing the praises—or harping on the importance, depending on perspective—of a solid, standalone enterprise data strategy. While certainly not a new concept, Government missions are wholly dependent on real time access/analysis of data (wherever it may be (legacy data centers or public cloud) to render insight to support operational decisions.

In this previous blog post we provided a high-level overview of Cloudera Replication Plugin, explaining how it brings cross-platform replication with little configuration. In this post, we will cover how this plugin can be applied in CDP clusters and explain how the plugin enables strong authentication between systems which do not share mutual authentication trust.

For all of the buzz surrounding both artificial intelligence and data-driven management, many companies have seen mixed results in their quest to harness the value of enterprise data. To avoid those pitfalls, we mixed best-of-breed and proprietary solutions to develop our enterprise data platform (EDP), focusing much of our attention on a combination of smart changes in technology, culture and process for data lakes.

Like most organizations, Yellowfin has a CRM tool. The data in your CRM should be able to help you understand how you’re selling and how you win. But everyone I speak to is frustrated by the analytics they get from their CRM. We realized very quickly that the reporting in our CRM tool wasn't meeting our needs, so we built our own solution.

For data analysts, business intelligence professionals, and CTOs to optimize and scale business operations, they must first understand the business data that is available to them. One of the best platforms to turn complicated data points from multiple platforms into a singular, coherent data set is Microsoft Power BI. However, you must first prepare the data sets to eliminate fragmentations and create structural consistency. This article explores how to prepare data for Microsoft Power BI.

Hortonworks DataFlow (HDF) 3.5.2 was released at the end of 2020. The new releases will not continue under HDF as Cloudera brings the best and latest of Apache NiFi in the new Cloudera Flow Management (CFM) product. Getting the latest improvements and new features of NiFi is one of many reasons for you to move your legacy deployments of NiFi on this new platform. To that end, we released a few blog posts to help you migrate from HDF to CFM.