Systems | Development | Analytics | API | Testing

Built with BigQuery: How Exabeam delivers a petabyte-scale cybersecurity solution

Exabeam, a leader in SIEM and XDR, provides security operations teams with end-to-end Threat Detection, Investigation, and Response (TDIR) by leveraging a combination of user and entity behavioral analytics (UEBA) and security orchestration, automation, and response (SOAR) to allow organizations to quickly resolve cybersecurity threats.

Technology Spotlight: Apache Iceberg

At Cloudera, we are committed to staying true to our open source roots and working well within the communities is critical to that. Since 2021, we have supported the growing Iceberg community with hundreds of contributions across Impala, Hive, Spark and Iceberg. We look forward to continuing the momentum as companies embrace the open lakehouse. General release now available in the Cloudera Data Platform.

Panther Brings Speed, Scale, and Flexibility to Security Analytics

Security practitioners are drowning in data, says Will Lowe, Chief Operating Officer at Panther. That’s why when Panther set out to create a new kind of security platform, it chose to build it around Snowflake. “We needed not just a technical partner, but a go-to-market partner. We needed alignment in the vision that security is a data problem. And Snowflake had that in spades.”

5 Embedded Analytics Pitfalls and How to Avoid Them

As the business world shifts towards an information economy, more companies are discovering the advantages of having a business intelligence (BI) solution for analytics. Embedded analytics software boosts an organization's main functionality by integrating BI tools and analytical capability directly into software applications, rather than as a separate third-party application.

Fraud Detection with Cloudera Stream Processing Part 1

In a previous blog of this series, Turning Streams Into Data Products, we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. We discussed how Cloudera Stream Processing (CSP) with Apache Kafka and Apache Flink could be used to process this data in real time and at scale. In this blog we will show a real example of how that is done, looking at how we can use CSP to perform real-time fraud detection.

Now in preview, BigQuery BI Engine Preferred Tables

Earlier in the quarter we had announced that BigQuery BI Engine support for all BI and custom applications was generally available. Today we are excited to announce the preview launch of Preferred Tables support in BigQuery BI Engine! BI Engine is an in-memory analysis service that helps customers get low latency performance for their queries across all BI tools that connect to BigQuery.

SaaS in 60 - Catalog Improvements

The Qlik Sense SaaS catalog can now include data that is stored in relational databases such as Oracle, SQL Server and Snowflake increasing data reuse, visibility and governance while expanding the types of content that data engineers and stewards can manage and distribute. It also simplifies data use as data consumers no longer need to setup data connections as they can simply browse for the data they need within the catalog.

Introduction to Cloudera Edge Flow Manager

This video is a 101 introduction about Edge Flow Manager (EFM), the Cloudera Edge Management (CEM) solution for managing and monitoring Apache MiNiFi agents at scale. The video goes through all the different views of the user interface to demonstrate and explain all of the features for designing flows, publishing flows to the agents, execute remote commands, monitoring the agents, etc.

Learn how BI Engine enhances BigQuery query performance

BigQuery BI Engine is a fast, in-memory analysis service that lets users analyze data stored in BigQuery with rapid response times and with high concurrency to accelerate certain BigQuery SQL queries. BI Engine caches data instead of query results, allowing different queries over the same data to be accelerated as you look at different aspects of the data.