By Mike.Hallett-Oracle on Aug 19, 2015
August 29th at 10 a.m. Pacific USA time – Partners and customers can join our webcast with Cloudera, Unlock Your Analytic Talent with the Visual Face of Hadoop
Oracle Big Data Discovery version 1.1 is now available. This release extends Oracle’s innovation in Big Data Analytics by bringing together the best open-source and Oracle technologies, enabling you to reach more of the market and address more of your clients’ analytics challenges.
Big Data Discovery now runs on Hortonworks HDP 2.2.4+, in addition to Cloudera CDH 5.3+. That makes BDD the first Spark-based big data analytics product to run on the top two Hadoop distributions, significantly expanding your market opportunity.
Customers can now access enterprise data sources via JDBC, making it easy to mash up trusted corporate data with big data in Hadoop. BDD 1.1 elegantly handles changes across all this data, enabling full refreshes, incremental updates, and easy sample expansions. All data is live, which means changes are reflected automatically in visualizations, transformations, enrichments, and joins.
Dynamic visualizations fuel discovery – but no product can include every visualization out-of-the-box. This release includes a custom visualization framework that allows customers and partners to create and publish any visual and have it behave like it is native to BDD. Combined with new visualizations and simpler configuration, this streamlines the creation of discovery dashboards and rich, reusable discovery applications.
Big Data Discovery is unique in allowing partners and customers to find, explore, transform, and analyze big data all within a single product. This release significantly extends BDD Transform, making it both easier and more powerful. New UIs make it easy to derive structure from messy Hadoop sources, guiding users through common functions, like extracting entities and locations, without writing code. Transformation scripts can be shared and published, driving collaboration, and scripts can be scheduled, automating enrichment. Transform also includes a redesigned custom transformation experience and the ability to call external functions (such as R scripts), providing increased support for sophisticated users.
BDD 1.1 supports Kerberos for authentication (both MIT and Microsoft versions); enabling authorization via Studio (including integration with LDAP) to support Single Sign-on (SSO); and providing security at both project and dataset levels. These options allow customers to leverage their existing security and extend fine-grained control to big data analytics, ensuring people see exactly what they should.
And if you wish to deep dive into Spark (although to use BDD, this is not needed), I suggest you check out the Cloudera Developer Training for Apache Spark.