Teradata (NYSE: TDC), the analytic data platforms, marketing applications, and services company, announced two acquisitions that accelerate the growth of its big data capabilities. One of them is Revelytix, the other being Hadapt.
IBM (NYSE: IBM) announced it is investing $3 billion over the next 5 years in two broad research and early stage development programs to push the limits of chip technology needed to meet the emerging demands of cloud computing and Big Data systems.
Getting right insights into big data at the right time is the key to big data analytics. Companies are using different tools to get these insights into big data with different success levels. What is more important is the availability of policies and framework for big data analytics.
Hadoop 2 has made real-time Big Data analytics easier than ever. With data growth enterprises need data analytics to get an actionable insight for historical data.
Big Data Projects have become an indispensable part of every organization owing to the useful business insights they provide. But in the current scenario, as the Big Data technologies are maturing, validation and testing of these Big Data projects is not an easy task. What organizations need at this point of time are solutions that can make Big Data application testing easy, efficient, and accurate.
Actian Corporation has launched the Actian Analytics Platform, an end-to-end analytics platform that enhances and extends advanced analytics directly on big data in the Hadoop Distributed File System (HDFS).
DataTorrent has announced the general availability of its product DataTorrent RTS. The product is developed on top of Hadoop 2.0 and allows companies to process massive amounts of big data in real time.
SnapLogic, the Elastic Integration Company, announced an expansion of its integration platform as a service (iPaaS) designed to make it easier to acquire, prepare and deliver big data. SnapReduce 2.0 enables SnapLogic to run natively on Hadoop as a YARN-managed resource (Yet Another Resource Negotiator) that elastically scales out to power next generation analytics.
Big Data Analytics is being used by businesses across different sectors to their advantage. Retail industry is no different. This is possible in the case of Retailers by getting crucial customer insights using big data analytics.
Big Data is becoming increasingly more complex, making the task of analysts and data scientists more difficult. Each time data is integrated, added, enriched, or transformed the results of the analysis can change. Traditional data analysis visualization products enabled analysts and data scientists to only visualize the final results. Any changes that had to be made had to wait until this stage – consuming precious resources and taking up valuable time.