In their transition to become digital businesses, many organizations are leveraging analytics to derive value from the vast amounts of data their businesses produce. Even for data science experts, putting together an analytics framework can be challenging and time consuming. Recognizing this challenge and leveraging our deep expertise in analytics technologies, TIBCO has launched the Accelerator for Apache Spark.
TIBCO is a leader in the analytics industry, developing technologies that enable companies to analyze data at rest and act on data in motion—something we call Fast Data. We’ve spent many years helping our customers solve some of the thorniest problems in the space and have first-hand insight on emerging use cases for analytics that have delivered real value to our customers.
There are some standard steps that are required as part of a big data effort that are simplified with this tool: interfacing with the myriad big data technologies that exist, capturing and acting on streams of data, and enhancing (both training and scoring) the models being applied for your application.
Accelerator for Apache Spark includes more than 40 ready-to-use building blocks to speed up implementations, and provides drag-and-drop functionality for business solution developers to efficiently work with powerful tools like H2O, HDFS, Avro, and TIBCO’s high performance runtime for R (TERR).
As Mark Palmer, our SVP and GM of Analytics, said when he introduced accelerators a few months back: “Accelerators can help get 80% of the basics of an application in place quickly, and then, innovate for the last 20% by adding your ‘secret sauce’—what makes your business unique.”
TIBCO is committed to helping our customers with their analytics efforts and our Accelerator for Apache Spark adds to our already existing library of Accelerators that includes our Connected Vehicles Accelerator, FX Dealing Accelerator, and our IoT focused Intelligent Equipment Accelerator.
Learn more on our TIBCO Community wiki and accelerate your analytics efforts today!