Financial Risk Analytics has evolved beyond a secondary regulatory and cost-focused perspective, to become a core part of businesses. Today, Risk Analytics provides a competitive edge by enabling businesses to efficiently use capital and manage risk exposures with higher confidence to make better informed and timelier business decisions. To learn more down this white paper.
Cisco and NetApp Deliver Simplified, Affordable Disaster Tolerance Solutions for SAP HANA Deployments
This document describes Cisco® and NetApp solutions that support disaster-tolerance capabilities for SAP HANA deployments. This comprehensive approach encompasses synchronous and asynchronous replication, a point-in-time backup strategy, and protection of data against corruption. Because management of disaster scenarios requires coordination, the Cisco and NetApp solution handles the failover of servers, networking, and storage components to quickly activate a disaster-recovery site.
NetApp Distributed Content Repository is a comprehensive solution to an organization’s unstructured data storage and archiving challenges and an easy path to handling big content in a private or public cloud. The solution is built upon NetApp StorageGRID software, running on industry standard x86 servers (virtualized for availability and flexibility) and NetApp E2600 series storage platform. Learn more by downloading this white paper.
Few industries have greater access to data around consumers, products, and channels than the retail industry. Data coupled with insights are at the heart of what drives this business. It’s a logical consequence then that retail is the vertical market that adopted big data and technologies like Hadoop earlier than many other industries. Retail started with diverse transactional data but is now much more sophisticated in the way technology is being applied toward gaining competitive advantage. Learn more by downloading this guide.
This technology guide is geared toward scientific researchers working at universities and other research institutions (e.g. NASA, JPL, NIH, etc.) who may benefit from learning more about how big data is meaningfully transformative in the way it can be applied to the data collection and analysis part of their projects. Further, we’ll illustrate how Dell big data technology solutions powered by Intel are actively helping scientists who are focused on their data, on their models and on their research results. Learn more by downloading this guide.
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Learn more by downloading this Guide to Predictive Analytics.
Parse.ly, a leading provider of audience insights for digital publishers and brands, announced the availability of the Parse.ly Data Pipeline, a live stream of user- and event-level data that is structured for sophisticated analysis and real-time data engineering projects.
Our friends over at Expert System conducted cognitive analysis of more than 430,000 Tweets about the Rio 2016 Olympic Games to discover and understand what was most discussed on social media – including sports, countries, athletes and impressions of the games in general.
Financial Risk Analytics has evolved beyond a secondary regulatory and cost-focused perspective, to become a core part of businesses. Today, Risk Analytics provides a competitive edge by enabling businesses to efficiently use capital and manage risk exposures with higher confidence to make better informed and timelier business decisions. Hence CEOs increasingly rely on their CFOs and their Chief Risk Officers (CROs) for strategic advice and active risk management.
The traditional HPC and commercial markets have been converging as established HPC users increase their use of newer analytics methods and commercial firms turn to HPC for mission-critical analytics problems that enterprise technology alone can’t handle adequately. Key verticals exploiting HPDA include financial services, healthcare/bioinformatics, energy, cybersecurity/fraud, manufacturing, online retailers and service providers, digital content creation, telecommunications, government, and academia. Key horizontal applications include simulation, fraud and anomaly detection, business intelligence/business analytics, machine learning/deep learning, affinity marketing, and advanced visualization.