Dell steps up analytics push with Statistica 13, new vertical services
The company's Analytics-as-a-Service line has gained several new industry-specific offerings
whatthingnews.com : Dell got a jump-start in the world of analytics software when it acquired StatSoft early last year, and on Tuesday it forged further ahead into the space with a new Statistica release and a variety of industry-specific services.
Announced at the company's Dell World conference taking place in Austin, Texas, this week, Statistica 13 updates the company's advanced analytics software platform with several key new capabilities. First and foremost is native distributed analytics, a feature that allows users to run analytics directly in the database where data resides.
"Usually people dip data out of the database or Hadoop cluster and bring it back to a smaller server or desktop for analysis there," said John Thompson, general manager for advanced analytics with Dell Software. "This allows you to take your analytical models to the data."
Users can build models and export them into different languages, including C, SQL or Java, Thompson explained. Then, they can transport them into the data environment of their choice.
For example, "you can now run Java models on Hadoop," he said. "This opens it up to allow people to run models on large amounts of data and also to transport models out to environments like the Internet of Things."
Besides the ability to work with full volumes of data rather than just subsets, the new capability also brings better privacy and security since data can remain behind the corporate firewall without needing to traverse any networks, Thompson said.
Also included in Statistica 13 are a revamped user interface, tighter integration with the R programming language, and a new stepwise model tool that progressively recommends optimum models for users.
The software is available now featuring native distributed analytics capabilities for Microsoft SQL Server databases; additional databases will be added later, Dell said.
As for the services portion of Dell's analytics news, the company is expanding its Analytics-as-a-Service line with several new industry-specific offerings.
One targeting the medical industry, for example, focuses on helping organizations identify cases of medical identity theft, unnecessary diagnostic services and incorrect billing. Others focus on scoring the likelihood of claim denial and churn management.
"It's all integrated and targeted for specific business problems, so time to market is going to be very quick," said Prasad Thrikutam, president and global head of applications for Dell Services. "It's also outcome-oriented, so you're not just throwing dollars at the problem and hoping something will come out."
acquired
StatSoft sells analytics, database management and integration software. Terms of the acquisition were not detailed.
StatSoft’s products provide data mining and analytics capabilities—such as identifying trends via social networks—designed to help companies grow and better make sense of structured and unstructured data across server and cloud resources. The company’s primary offering is Statistica, which uses statistics and algorithms for data analysis and predictions.
Dell said in an announcement Monday that the StatSoft software will be packaged along with Dell x86 servers.
Dell is primarily is a hardware company, but with margins in x86 servers and PCs dwindling, has turned its focus to software over the last three years. The company acquired a range of software companies including Quest Software, Wyse, Boomi, AppAssure, SonicWall, Clerity and Make.
Dell has had trouble integrating into its core operations companies like Wyse, which continues to sell its cloud hardware and software while being largely disconnected from Dell’s other units.
Dell already sells the Kitenga analytics software, which is part of the Quest Software unit. StatSoft’s products can work in conjunction with the Kitenga offering, and add features like natural language processing to data analysis, said Matt Wolken, vice president and general manager of information management at Dell, in a blog entry about the acquisition.
Third-party software is also being packaged in Dell servers, and StatSoft tools will work with SAP’s Hana and databases from Oracle and Microsoft, Wolken said.
Some of StatSoft’s customers include Pepsi, Lenovo and Schlumberger.
R programming language gaining ground on traditional statistics packages
The R programming language is quickly gaining popular ground against the traditional statistics packages such as SPSS, SAS and MATLAB, at least according to one data statistician who teaches the language.Muenchen gauged the popularity of statistical software packages by tracking how often they have been used for published scientific research and the number of mentions they get in online discussion forums, blogs, job listings and other sources.
Scholarly citations are a “good leading indicator of where things are headed,” Muenchen wrote. Students who learn to use these software packages later go on to use them in their professional careers, either in academia or industry.
In his latest survey, Muenchen found that researchers continue to do most of their work on traditional software packages, namely SAS’s and MATLAB’s self-named package, as well as IBM’s SPSS.
SPSS led the pack with over 75,000 citations in scientific papers, which were culled through a search on Google Scholar. SAS follows in second place with almost 40,000 citations. R was used in well over 20,000 research projects.
Moreover, when Muenchen examined the number of citations since 1995, he found that SPSS citations have declined since 2007. SAS trailed SPSS in usage, peaking in 2008. The use of R, in contrast, has been growing dramatically, faster than other packages such as Statistica and Stata.
“Extending the downward trend of SPSS and the upward trend of R make it likely that sometime during the summer of 2014 R became the most dominant package for analytics used in scholarly publications,” Muenchen wrote. “Due to the lag caused by the publication process, getting articles online, indexing them, etc. we won’t be able to verify that this has happened until well into 2015.”
R is an open-source functional programming language designed for statistical computing and graphics .
Muenchen, a certified statistician who manages the research computing support at the University of Tennessee, may not be the most impartial person to declare a victory for R—he also works as an R instructor on behalf of Revolution Analytics. But he has also been long recognized as an expert in computer analytics, contributing code to SAS, SPSS and various R packages. He has also served on the advisory boards of SAS and SPSS before it was acquired by IBM in 2009.
Muenchen did not speculate in the blog post summarizing his findings about why R is gaining popularity.
That implementations of R are available as open source—and can be downloaded by researchers starting on a project at no cost—may be a factor in its popularity, said Al Hilwa, who covers enterprise software development for IT analyst firm IDC.
“Like many open source projects with active communities, R has gotten better with time,” Hilwa wrote in an email. “I think what we are seeing are trends that are long in motion. Acquiring of developer skills around programming languages takes time and so what we are seeing is a delayed effect reflected in actual use data.”
In his study, Muenchen did not distinguish between which R distributions users cited, which could be Revolution Analytics’ open-source or enterprise editions, or the open-source volunteer-led R Project.
Other indicators also seem to point to the growing popularity of R, Muenchen noted. The number of job postings on Indeed.com requiring R skills has surpassed those asking for SPSS experience, though they are still fewer than the number of ads calling for SAS expertise. The number of books and discussion forums devoted to R exceeds those for either SAS or SPSS.
Hilwa also noted that there is increasing demand for workers with statistical and data analysis skills in general, which can be seen as the “tide that lifts all boats in this ecosystem of languages,” he wrote.
