The Cloudera Data Platform One bundles all the tools required for data analysis and exploration as Software-as-a-Service based on the Lakehouse architecture.
The provider Cloudera, which specializes primarily in tools for ETL processes, data engineering, and data analysis and visualization, is expanding its Cloudera Data Platform (CDP) with an all-in-one data service in the cloud. As Software-as-a-Service based on the Lakehouse architecture, the new Cloudera Data Platform One is intended to combine all the necessary tools in one service that companies need to explore and analyze all data.
All-in-one data service with a low barrier to entry
With the new platform, Cloudera wants to pave the way to the cloud for all companies that are pursuing a data-driven business strategy. The services bundled in CDP One cover the entire data lifecycle management including cloud storage and computing as well as machine learning and analytics of streaming data. According to the announcement, the SaaS offer is designed for data professionals and experienced developers in companies, but a portfolio of low-code tools is intended to keep the barrier to entry into cloud-based data analysis and exploration as low as possible. As a result, users should benefit from shorter implementation times when transforming to a Lakehouse architecture in the cloud and at the same time be able to rely on comprehensive data security, as Cloudera’s CTO Ram Venkatesh promised at the presentation of CDP One.
On the way to the Enterprise Data Cloud
Cloudera Data Platform One complements the CDP, which originally emerged from the merger of Cloudera with Hortonworks, with another building block on the way to the Enterprise Data Cloud. The company has also gradually expanded its portfolio of data services in recent years through acquisitions such as the takeover of Arcadia Data, a specialist for real-time analyzes and AI-supported business intelligence. This includes the managed Apache Spark service CDP Data Engineering on Kubernetes, which provides tools for ETL processes, data pipeline orchestration, automation and monitoring.
