A quick conversation with most Chief Information Security Officers (CISOs) reveals they understand they need to modernize their security architecture and the correct answer is to adopt a machine learning and analytics platform as a fundamental and durable part of their data strategy. However, many CISOs fear deployment of an initial use case will be somewhat daunting. Cloudera has partnered along with Arcadia Data and StreamSets to make it easier than ever for CISOs to take the first step and deploy basic use cases leveraging data sources common to many environments.
Today, we’re really excited to announce the latest innovation from Cloudera and Informatica’s partnership. Companies are increasingly moving their data operations into the cloud. With both companies focusing on helping customers derive business insights out of vast amounts of data, our new joint offering will dramatically simplify leveraging cloud-native infrastructures for big data analytics.
Last May, Cloudera announced Cloudera Altus, a new platform-as-a-service (PaaS) offering in the cloud for big data analytics,
What is SDX?
Shared Data Experience — SDX — is Cloudera’s secret ingredient that makes it possible to deploy Cloudera’s four core functions (Data Engineering, Data Science, Analytic DB, Operational DB) on a single platform.
Why does that matter?
First, each of those core functions is essential to any modern enterprise business.
- Data Engineering enables the business to run batch or stream processes that speed ETL and train machine learning models
- Data Science enables the business to do exploratory data science at big data scale with full data security and governance
- Analytic DB delivers the fastest time-to-insight with the flexibility and agility to run in any environment and against any type of data.
Technology-focused discussions about genomics usually highlight the huge growth in DNA sequencing since the beginning of the century, growth that has outpaced Moore’s law and resulted in the $1000 genome. However, future growth is projected to be even more dramatic. In the paper “Big Data: Astronomical or Genomical?”, the authors say it is estimated that “between 100 million and as many as 2 billion human genomes could be sequenced by 2025”,
Organizations analyze logs for a variety of reasons. Some typical use cases include predicting server failures, analyzing customer behavior, and fighting cybercrime. However, one of the most overlooked use cases is to help companies write better software. In this digital age, most companies write applications, be it for its employees or external users. The cost of faulty software can be severe, ranging from customer churn to a complete firm’s demise, as was the case with Knight Capital in 2012.