DataStax Enterprise Analytics integrates real-time and batch analytics capabilities directly in DataStax Enterprise (DSE). With DSE Analytics you can easily generate ad-hoc reports, target customers with advanced personalization and process real-time streams of data to create intelligent applications. Because DSE Analytics is a core capability of DSE you can utilize powerful transactional, search, and graph functionality without having to implement the complicated and time consuming processes of keeping multiple data silos in sync. DSE Analytics frees you to focus on delivering transformative real-time value at the scale your business demands.
Build Intelligent Applications
Building applications that are capable of understanding data in real-time and engaging with the world at scale is a requirement for the new digital economy. Users expect personalized behavior. Sophisticated fraud prevention requires adaptive capabilities. The Internet of Things (IoT) needs real-time aggregation and alerting, and businesses must understand the various ways that customers interact with your company. DSE Analytics incorporates powerful real-time and batch analytics capabilities that makes it easy to create this intelligent behavior. Whether your applications need personalization, fraud prevention, IoT, or Customer 360° capabilities, DataStax Enterprise provides you the scale and tools necessary to quickly create intelligent applications.
“To provide quick feedback loops for customers, analytics needs to be
in real-time, alongside historical data. With data being pushed on the edge,
recommendations and personalisation had to have analysis done in near
real-time at the point of interaction, or at each transactional action or event.”
Real-Time and Batch Analytics
DataStax Enterprise uses an enhanced version of the industry standard Apache Spark™ project to provide both real-time and batch analytics functionality. The Spark toolset lets you write code once and then use it for both real-time and batch workloads. Streaming data can be analyzed, summarized, or filtered and then persisted to the highly available Cassandra database at the core of DSE. Once the data has landed in Cassandra it can be further analyzed via Spark, Spark SQL, and the rest of the Spark ecosystem of tools. Using open tools makes it easy to tap into a broad ecosystem; you can build upon the best tools and libraries available to quickly deliver new features.
British Gas Connected Homes uses DataStax Enterprise Analytics to
power its Hive smart thermostat project and MyEnergy smart meter products.
Meter data from 600,000 customers is collected in DataStax Enterprise
either daily or half hourly and processed with Spark to determine how energy
is spent. Connected Homes found Spark was 10 to 100 times faster
than Hadoop in processing the workload.
Integrated, Targeted, Fast
Most analytics tools require you to scan vast amounts of data that may or may not be relevant to the end result that you’re trying to achieve. Because DSE Analytics is tightly integrated into the database, your application can intelligently target relevant data using the CQL query language and search functionality of DSE. Real-time jobs are able to retrieve historical information to enrich the user experience, and create intelligent real-time behavior and analytical reports return in seconds instead of minutes or hours.
“With transaction, analytics and search all in the same cluster, we can quickly find and analyze workloads of any size quickly without taxing compute resources.”
Flexible Workload Management
DSE provides flexible workload management to isolate analytics jobs to dedicated resources. These workload isolation capabilities allow you to run intensive analytics processes without harming latency sensitive applications. DSE Analytics also allows you to share and allocate resources across teams so that multiple analytic jobs can run in parallel.
Works with Existing Tools
DSE Analytics enables customers to leverage existing investments in both legacy and post relational tools. DSE Analytics allows you to easily stream data to or from your existing databases including: Hadoop, HDFS, HBase, Oracle, MySQL, IBM DB2, and external Spark clusters. Because DSE Analytics also provides ODBC and JDBC compatible interfaces you can easily leverage your existing investments in business intelligence tools such as Tableau and Zoomdata.
As part of the DSE platform, DataStax Enterprise Analytics includes around-the-clock support from the distributed systems experts at DataStax, which delivers the confidence needed to run and maintain production systems at scale. Support also includes formal end-of-life policies, certified software updates, hot-fixes, and bug escalation privileges.