WHITE PAPER:
This white paper shows how mathematical optimization provide tools that deliver significant competitive advantage for solving the most challenging problems encountered in finance, including risk management, operational cost, and product innovation.
WHITE PAPER:
Optimization is unique simply by being the mathematical discipline focused on efficiency. Along with statistics and predictive analytics, it is one of the two mathematical disciplines used most frequently in the world of business. Download this white paper to learn how to solve your toughest planning and scheduling problems.
WHITE PAPER:
A full market perspective is difficult because of fragmented liquidity. Many securities are traded on more than one exchange or alternative trading venue. Knowing when, where and how to trade can be a challenge, and it’s getting harder all the time as the markets evolve.
WHITE PAPER:
In their latest book, Thomas Davenport, Jeanne Harris and Robert Morison show how companies apply analytics in their daily operations. We see examples of analytics at work within core processes in a variety of business areas. Read this white paper to learn how embedding analytics into your organization's processes can help you.
WHITE PAPER:
With test management and statistical analysis integrated into an automated system, organizations can target problem components and processes in less time with more accuracy, reducing the cost of manufacturing quality products.
WHITE PAPER:
The following white paper introduces a mobile application development solution that can allow you to build, deploy, utilize, and capitalize on mobile applications without having to rely on IT for help.
WHITE PAPER:
Access this exclusive resource to find out how the combination of HP's converged infrastructure and Red Hat's virtualization software create the perfect platform for consolidating your Linux systems.
WHITE PAPER:
Explore research done by Gartner to find out how in-memory computing will impact ERP during the next 5 years, so businesses can plan accordingly.
