InetSoft has announced the availability of Style Intelligence version 12.2, the company’s data intelligence platform. In conjunction, the vendor has also updated its sub products Style Scope and Style Report. Version 12.2 offers two major feature enhancements, including full maturation of HTML5 for browser-client access, and full integration with Hadoop as the foundation for Big Data use. The data intelligence platform servers both the enterprise and solution providers with cloud-ready, fully scalable granular security, multi-tenant support and a variety of integration points.
Administrators can install a built-in dedicated Spark or Hadoop cluster or point to an existing shared cluster, opening standards-based agile architecture that allows organizations to mature into Big Data over a period of time as data volumes expand. InetSoft’s advanced visual analytics engine automates the configuration and management of Big Data clusters according to user-defined analytics. What this does is to to reduce the skills required to deliver Big Data to the users who need it most.
Style Intelligence is a data intelligence platform, powered by a data mashup ending that enables fast and flexible transformation of data from disparate sources. At the development level, a unified interface allows for easy and advanced data manipulation and design of interactive dashboards, visual analyses, and published reporting. At the consumption level, self-service is maximized for a range of users, from casual business or consumer-type browsers to power users and data scientists.
InetSoft’s CMO Mark Flaherty sums up the new release: “This is an exciting release because it further lowers the TCO of our solution and widens the end-user adoption possibilities. Getting end-user support cost savings by upgrading a version should be very welcome news for our installed base. In term of the Spark technology move, this is compelling not only because of its attractiveness to organizations who already use Spark, but because organizations with “small data” environments now have such as an easy path to growing into big data ones as their own datasets grow organically in size. Not only do they not have to worry about outgrowing a solution, but they don’t have to worry about later spending on new expertise and tools to accommodate their growth.”
- Analytics and Data Science News for the Week of September 30; Updates from DataRobot, SAS Software, Vyasa, and More - September 29, 2022
- The 10 Best Data Scientist Certifications Online for 2022 - September 29, 2022
- The 12 Best Data Scientist Courses and Online Training for 2022 - September 29, 2022