Re: What about Personalized Big Data Analytics?
Analytics tools and BI systems run on servers, but these systems are generally not scaled to handle big data. More often than not, these systems draw data from data warehouses or data marts. Increasingly, a larger-scale "platform" such as a massively parallel processing (MPP) database management system or Hadoop cluster is required to handle the volume and variety of data. Some analytics vendors, notably SAS but including others, are developing their own in-memory cluster software or implementations on top of Hadoop, but the vast majority of clients use analytics and BI software in combination with data-management platforms from third-party vendors like those covered in the collection above.
Confusing matters, many vendors above offer analytic capabilites -- IBM has SPSS and Cognos; SAP has BusinessObjects and Predictive Analysis; Oracle, Pivotal, and Teradata tap advanced SQL analytics, R and various partnerships with analytics vendors including SAS, etc. -- but they're not included in this collection because of those capabilites.
There are many options for smaller companies -- including cloud, price-competitive upstart vendors, and open source options. But where this is great data volume, variety, and velocity, there's a need for a high-scale platform or platforms to serve as the place where the analysis gets done (as with in-database or in-Hadoop analytics) or as the place from which subsets of data are drawn or analyzed (as in the case of Hadoop or data warehouse integration).
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10/9/2017 | 5:35:16 AM