Fine grained access control (FGAC) with Spark Apache Spark with its rich data APIs has been the processing engine of choice in a wide range of applications from data engineering to machine learning, but its security integration has been a pain point. Many enterprise customers need finer granularity of control, in particular at the column […]
Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake. […]
Data holds incredible untapped potential for Australian organisations across industries, regardless of individual business goals, and all organisations are at different points in their data transformation journey with some achieving success faster than others. To be successful, the use of data insights must become a central lifeforce throughout an organisation and not just reside within […]
Please join us on March 24 for Future of Data meetup where we do a deep dive into Iceberg with CDP What is Apache Iceberg? Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. By being a truly open […]
Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. This unprecedented level of big data workloads hasn’t come […]
Since the release of Cloudera Data Engineering (CDE) more than a year ago, our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. In working with thousands of customers deploying Spark applications, we saw significant challenges with managing Spark as well as automating, delivering, […]
