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SAS, IBM and SAP are clear leaders in the big data analytics space, specifically predictive analytics, according to a recent report from Forrester Research.
Forrester’s evaluation of general-purpose big data predictive analytics solutions reveals these three leaders, along with five strong performers and two contenders. The Leaders in this Forrester Wave offer a rich set of algorithms to analyze data, architectures that can handle big data, and tools for data analysts that span the full predictive analytics life cycle. SAS and IBM stand out above the others in the study, but each of the 10 vendors evaluated provide unique points of differentiation that many customers will find attractive, Forrester said.
The report says that among the 10 vendors evaluated, SAS is “an analytics powerhouse” and, along with IBM, is an “unshakable leader” in the analysis of big data predictive analytics solutions. The ratings were based on three categories, and SAS scored highest among all vendors in each: current offerings, strategy and market presence.
“Since 1976, SAS has provided enterprises with the industry’s most powerful analytics, which continue to support the world’s largest data sets, now called big data,” Jim Davis, SAS senior vice president and chief marketing officer, said in a statement. “With innovative new products such as SAS High-Performance Analytics Server, SAS Visual Analytics and SAS DataFlux Event Stream Processing Engine, we are leading the charge to meet new and fast-evolving customer needs.
“Regardless of data volume, analytics maturity or company size, SAS helps organizations uncover insight, and while every organization may not have big data, they all have big data analytics problems,” Davis said.
SAS, with its 36-year history of providing analytics software, was a leader in the evaluation because it scored well in all categories. Its SAS Enterprise Miner tool is easy to learn and can run analysis in-database or on distributed clusters to handle big data, Forrester said. IBM’s Smarter Planet campaign and acquisitions of SPSS, Netezza and Vivisimo represent its commitment to big data predictive analytics. IBM’s complementary solutions, such as InfoSphere Streams and Decision Management, strengthen the appeal for firms that wish to integrate predictive analytics throughout their organization.
Meanwhile, SAP is a newcomer to big data predictive analytics but is a leader due to a strong architecture and strategy. SAP also differentiates by putting its SAP HANA in-memory appliance at the center of its offering, including an in-database predictive analytics library (PAL), and offering a modeling tool that looks a lot like SAS Enterprise Miner and IBM SPSS Modeler, Forrester said.
SAS, IBM Lead in Predictive Analytics
A tier below the leaders, Forrester listed Tibco, Oracle, StatSoft and KXEN as strong performers with unique approaches. In general, the strong performers had lower architecture scores than the Leaders. Tibco’s Spotfire advanced data visualization tool offers core support for the S+ and R programming languages, which makes it attractive to data scientists who know those languages, Forrester said. Oracle’s solution centers on offering in-database R and the strength of its in-database analytics technology.
StatSoft has a comprehensive number of analysis algorithms and is very strong in manufacturing use cases. KXEN collapses the normal predictive analytics life cycle by automating the predictive model discovery process; it also offers strong social network analysis.
Coming in a tier below the strong providers are the contenders, which include Angoss, Revolution Analytics, and Salford Systems and have a narrower focus, Forrester said. Despite the narrower focus of these smaller vendors, customers have good reason to consider them, Forrester said.
“Angoss offers the best tooling for decision trees that we have seen and offers cloud solutions that firms can use to improve results quickly,” the Forrester report said. “Revolution Analytics aims to be the de facto commercial provider of solutions based on the very popular open-source statistics programming language R; other vendors in this evaluation offer or plan to offer R-based solutions.
“Salford Systems claims superior implementations of analysis algorithms, including CART, MARS, TreeNet and random forests; it has made a strong name for itself in particular among data scientists who have an interest in the algorithms that Salford supports,” the Forrester report said.
The Forrester report also calls out Oracle to do better. “Oracle can do better than R,” the report said. “Oracle’s solution centers on in-database analytics capabilities and prepackaged solutions within its widely adopted enterprise RDBMS [relational database management system], applications, and Exadata appliance rather than predictive analytics tools that are database-agnostic.”