Industry News

Frontline offers Excel users ‘total solution’ for analytics

Frontline Systems is now shipping Version 12.5 of its Solvers for Excel, including a new flagship integrated product, Analytic Solver Platform. V12.5 also includes new versions of Risk Solver Platform, the leading tool for simulation risk analysis, conventional and stochastic optimization in Excel; subsets Premium Solver Platform, Premium Solver Pro and Risk Solver Pro; and XLMiner, the leading data mining add-in for Microsoft Excel. Analytic Solver Platform integrates all the capabilities of all these products, and adds new features such as visual data exploration and data mining methods applied to Monte Carlo simulation trial data.

“Our tagline for Analytic Solver Platform is ‘no-compromise analytics in Excel’,” says Daniel Fylstra, Frontline’s president and CEO. “Users enjoy the ease of use of Excel, and leverage their spreadsheet model-building experience, but they don’t compromise at all on functionality or performance.”

Analytic Solver Platform incorporates many of the most powerful algorithms for optimization, simulation and data mining available, and exploits new technology in CPUs, GPUs and cloud servers to a greater degree than “enterprise analytics software” costing five to 10 times more.

Frontline’s Solvers for Excel are upward compatible from the Solver included in Excel, which Frontline developed for Microsoft, and improved in Excel 2010 for Windows and Excel 2011 for Macintosh. Users can solve problems hundreds to thousands of times larger than the basic Excel Solver, at speeds anywhere from several times to hundreds of times faster, and they can solve completely new types of problems. Frontline’s Solvers V12.5 work with Excel 2007, Excel 2010 and Excel 2013, which recently became available to Microsoft’s corporate customers and will be available at the retail level in early 2013.

Analytic Solver Platform is the first software to bring the power of data mining and visual data exploration to the analysis of Monte Carlo simulation trial data. Frontline’s and other vendors’ Monte Carlo software has offered histograms, tornado charts and descriptive statistics summarizing simulation results, but they’ve had only limited visualization for multivariate data, and aside from basic sensitivity analysis, they have lacked tools to discover patterns in simulation data. This has changed in Analytic Solver Platform, which makes all the data visualization and algorithmic tools of XLMiner available for analysis of simulation trial data placed on a worksheet.

Students ‘Achieving Dream’ with SAS, analytics

For the first time, the 2012 cohort of Achieving the Dream Community Colleges is able to apply powerful SAS analytics and visualization software to evaluate student data in more effective ways. Through this new collaboration between Achieving the Dream and SAS, participating colleges identify struggling students (or those likely to struggle) and implement interventions to help them succeed.

All colleges in the National Reform Network 2012 Cohort (representing an estimated 275,000 students from 10 states) have access to SAS. The colleges will analyze three years of longitudinal student data. The results help them to identify students having difficulties, and intervene via evidence-based supports.

To assist with the implementation, dubbed “JumpStart for Institutional Research,” Achieving the Dream has engaged the Center for Applied Research (CFAR) at Central Piedmont Community College (Charlotte, N.C.) to provide technical assistance and programming support.

“Many Achieving the Dream Community Colleges lack the IT resources to meet the rigorous data standards necessary to track performance,” says Dr. Nicole Melander, Achieving the Dream’s Chief Technology Officer. “Through SAS and CFAR, we are offering a complete solution to support institutional research, reporting, and planning.”

SAS’ data integration, reporting and analytics are used by institutional research departments around the world to identify the best candidates for admission, predict which students are at the greatest risk of attrition or determine the optimum number of resources for incoming students.

“SAS is committed to supporting data-informed decisions to improve education,” says Armistead Sapp, senior vice president, SAS Education Practice. “By improving institutional research, our partnership with Achieving the Dream Colleges should increase student success.”

IBM system fends off fraud, security threats

Advanced attacks, widespread fraud and the pervasive use of social media, mobile and cloud computing are drastically altering the security landscape. As organizations increasingly need to manage big data, the way that corporate data needs to be protected is rapidly changing.

To aid in the detection of stealthy threats that can hide in the increasing mounds of data, IBM recently announced IBM Security Intelligence with Big Data, combining leading security intelligence with big data analytics capabilities for both external cyber security threats and internal risk detection and prevention. IBM Security Intelligence with Big Data provides a comprehensive approach that allows security analysts to extend their analysis well beyond typical security data and to hunt for malicious cyber activity.

This new solution combines real-time correlation for continuous insight, custom analytics across massive structured data (such as security device alerts, operating system logs, DNS transactions and network flows) and unstructured data (such as e-mails, social media content, full packet information and business transactions) and forensic capabilities for evidence gathering. The combination helps organizations address the most vexing security challenges, including advanced persistent threats, fraud and insider threats.

Key capabilities include:

  • Real-time correlation and anomaly detection of diverse security and network data
  • High-speed querying of security intelligence data
  • Flexible big data analytics across structured and unstructured data – including security, email, social media, business process, transactional, device and other data
  • Graphical front-end tool for visualizing and exploring big data
  • Forensics for deep visibility into network activity