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Like most companies of its size, Cisco Systems uses forecasts to help it direct resources. The accuracy and timeliness of those forecasts is critical, but keeping the predictive models that drive them up-to-date was a time-consuming task. So when the $47-billion company found new machine learning technology that could significantly speed up the training and scoring of those predictive models, it jumped at the chance. Cisco maintains a collection of 60,000 propensity to buy (P2B) models that it uses to Read more…
Big organizations have traditionally run analytics on-site, for a number of reasons, including data security concerns. But the rise of flexible cloud deployment models and the rapid pace of product development are helping cloud offerings to chip away at on-site deployments, especially for analyzing data that originates in the cloud. The IT world has not been the same since Amazon Web Services first took to the Net way back in 2006. Suddenly, a business of any size had an easy Read more…
This fall, thousands of budding data scientists around the country will begin their march toward advanced degrees–and the near certainty of multiple job offers upon graduation. At least seven new graduate-level programs are set to fire up at colleges and universities around the country, while a handful of new undergraduate programs are also popping up to give data scientists a head start on their schooling. The demand for data scientists remains extremely high as companies across all industries race to Read more…
A lot has been made of Hadoop becoming the singular control point for analytics, effectively usurping the enterprise data warehouse (EDW). The recent quest to integrate SQL into Hadoop is an example of that. But a better role for Hadoop is emerging that has it working hand in hand with existing EDW implementations in support of a hybrid big data analytics architecture. The hype level around Hadoop continues to run high as the big data wave keeps getting bigger. The Read more…
Don’t look now, Spark, but the big dog in the data analytics space, SAS, is staking an in-memory claim in Hadoop. Over the past two months, the North Carolina analytics giant has quietly given data scientists powerful new tools for building, managing, and running predictive and prescriptive data models within the confines of Hadoop. The need for speed on Hadoop has given rise to in-memory frameworks, such as Apache Spark, that are able to process data much faster than the Read more…
News In Brief
There has been much media coverage lately about standardized testing in American schools as well as fundamental changes to college entrance exams. But employers also have issues preventing cheating on professional certification and licensing exams.
The best way to boost your salary in 2014 may be to learn a new data analytics tool. According to the 2013 Data Science Salary Survey from O’Reilly, there was a strong correlation between data scientists and analysts who used the highest number of tools and those who had the highest salaries. What’s more, those who used open source tools, such as R and Hadoop, tended to bring home more bacon than those who used commercial products, such as SAS and Teradata.
Big data may appear to be a new trend, and refer to volumes, velocities, and variability that didn’t exist a few years ago. To some extent that’s true. But in the biggest companies, big data is really just a continuation of a decades-old trend toward “more data.” As these companies bring new technologies such as Hadoop and in-memory processing into their data centers, a new approach to building analytic systems is emerging, which is called Analytics 3.0.
Analytics are clearly on the rise as a transformational business technology, suggests research by SAS and MIT Sloan Management Review.
While the art and science of data governance is nothing new, organizations in the era of big data are finding themselves facing some unprecedented challenges. Some argue that not adapting to new needs could cost companies big money, not to mention their precious data.
This Just In
Utilities lack a strong pipeline of data scientists to tackle tough industry-business concerns. Analytics leader SAS has stepped up with a research and software grant, including energy forecasting technologies, to the University of North Carolina at Charlotte’s Energy Production Infrastructure Center (EPIC). Multidisciplinary engineering coursework combined with practical data applications are expected to attract new students to the field.
As organizations seek more insight from their data, the ability to organize and manage the data pouring in from an ever-growing list of sources is critical. To help organizations better access, manage and use data from any source, SAS has updated its SAS Master Data Management and SAS Federation Server software.
With its new SAS In-Memory Statistics for Hadoop, SAS is rapidly becoming the analytics platform of choice for the Hadoop open source framework, considered the future of big data.
Here’s more proof that big data and analytics are white hot: The world’s premier analytics conference, SAS Global Forum, has achieved record registration this year.
Data Science Technologies (DST), a subsidiary of StorIT Distribution and a pioneer in the Big Data Analytics solutions and services space, today announced its inaugural event on Big Data Analytics for customers and partners on March 18, 2014 at The Westin Mena Siyahi in Dubai. The event titled ‘The Big Data Analytics Power Lunch’ is a joint effort by DST and SAS to offer customers complete insights into harnessing their structured and unstructured, optimizing this data to grow their business further and demonstrate the features and benefits of using SAS Visual Analytics.