Users today are asking ever more from their data warehouse. This is resulting in advancements of what is provided by the technology, and a resulting shift in the art of the possible. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers.
With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.
Cloudera services logs offer a breadth of information to assist in cluster maintenance; from assisting in security checks, auditing tasks, and validation for performance tuning and testing tasks – to name a few. However, log records generated by these services do not hold the same value for every organisation.
The customer has never been more right. Across industries, customers have become conditioned to demand not only near-instant responses to their needs but that their needs be anticipated in advance. Financial institutions are not given a pass, despite a competitive landscape flooded with regulation and privacy considerations. The customer still has expectations for a personalized, timely, and relevant experience.
At Cloudera Fast Forward we work to make the recently possible useful. Our goal is to take the incredible data science and machine learning research developments we see emerging from academia and large industrial labs, and bridge the gap to products and processes that are useful to practitioners working across industries.
Growing up, were you ever told you can’t have it all? That you can’t eat all the snacks in one sitting? That you can’t watch the complete Back to the Future trilogy as well as study for your science exam in one evening? Over time, we learn to set priorities, make a decision for one thing over the other, and compromise. Just like when it comes to data access in business.
Cloudera and Dell/EMC are continuing our long and successful partnership of developing shared storage solutions for analytic workloads running in hybrid cloud.
Replication (covered in this previous blog article) has been released for a while and is among the most used features of Apache HBase. Having clusters replicating data with different peers is a very common deployment, whether as a DR strategy or simply as a seamless way of replicating data between production/staging/development environments.
The Insurance industry is in uncharted waters and COVID-19 has taken us where no algorithm has gone before. Today’s models, norms, and averages are being re-written on the fly, with insurers forced to cope with the inevitable conflict between old standards and the new normal.
Today we are introducing a new series of blog posts that will take a look at recent enhancements to Apache Impala. Many of these are performance improvements, such as the feature described below which will give anywhere from a 2x to 7x performance improvement by taking better advantage of all the CPU cores. In addition, a lot of work has also been put into ensuring that Impala runs optimally in decoupled compute scenarios, where the data lives in object storage or remote HDFS.
