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Published By: TIBCO Software     Published Date: Jul 22, 2019
Connected Intelligence in Insurance Insurance as we know it is transforming dramatically, thanks to capabilities brought about by new technologies such as machine learning and artificial intelligence (AI). Download this IDC Analyst Infobrief to learn about how the new breed of insurers are becoming more personalized, more predictive, and more real-time than ever. What you will learn: The insurance industry's global digital trends, supported by data and analysis What capabilities will make the insurers of the future become disruptors in their industry Notable leaders based on IDC Financial Insights research and their respective use cases Essential guidance from IDC
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TIBCO Software
Published By: Pega     Published Date: May 25, 2016
IT leaders working on customer service projects must display an incredible amount of diligence. An organization’s CRM system has become its lifeline to customers, but as customer needs evolve so has the requirements of CRM. According to Gartner, today’s CRM solution must include a laundry list of capabilities outside its traditional core functionality including: native mobile support of the vendor's customer service and support business applications; real-time analytics; industry-specific functionality and workflow; context mining of voice and text; scalable cloud-based systems; social media engagement; suggested next agent action; multimodal capabilities, such as chat within mobile self-service; and even co-browsing. Gartner surveyed the CRM field and evaluated each vendor including Pegasystems. Download this Gartner Magic Quadrant analysis and gain a better understanding each vendors’ CRM Customer Engagement Center solutions.
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best practices, customer support, business intelligence, business optimization, customer engaement
    
Pega
Published By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: SAS     Published Date: Oct 22, 2015
The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics. To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.
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SAS
Published By: SAS     Published Date: Nov 04, 2015
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management
    
SAS
Published By: Oracle     Published Date: Aug 08, 2013
As social media use has grown, an urgent need has emerged to correlate the information generated through social data with existing consumer information, and integrate it with sophisticated data management systems. This white paper describes how organizations can blend social insights with more-traditional data in an integrated customer data hub to optimize social strategies and create outreach efforts, new products, and campaigns grounded in real-time, repeatable, automated, and scalable analysis.
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social media, business intelligence, customer hub, crm, oracle, knowledge management, data management, business technology
    
Oracle
Published By: Riverbed     Published Date: Jul 17, 2013
Riverbed® Cascade Shark provides continuous, high-speed packet capture to ensure that packet-level information is available when needed for granular, real-time and post-event forensic analysis. Based on high-performance 1GbE and 10GbE capture cards, Cascade Shark is capable of sustained line-rate, multi-gigabit per second recording of network traffic.
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cascade shark, datasheet, riverbed, cascade, riverbed cascade, high-performance, sustained line-rate, network traffic
    
Riverbed
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
"With the introduction of Oracle Database In-Memory and servers with the SPARC S7 and SPARC M7 processors Oracle delivers an architecture where analytics are run on live operational databases and not on data subsets in data warehouses. Decision-making is much faster and more accurate because the data is not a stale subset. And for those moving enterprise applications to the cloud, Real-time analytics of the SPARC S7 and SPARC M7 processors are available both in a private cloud on SPARC servers or in Oracle’s Public cloud in the SPARC cloud compute service. Moving to the Oracle Public Cloud does not compromise the benefits of SPARC solutions. Some examples of utilizing real time data for business decisions include: analysis of supply chain data for order fulfillment and supply optimization, analysis of customer purchase history for real time recommendations to customers using online purchasing systems, etc. "
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Oracle PaaS/IaaS/Hardware
Published By: RelayHealth     Published Date: Apr 01, 2013
RelayHealth's Vice President, Business Analytics, Jason Williams examines how healthcare organizations can better set strategies by focusing on key decision points and adding data from real-time sources to what they have already collected.
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ecosystem, healthcare, real-time data, data, analysis, decision making, business analytics
    
RelayHealth
Published By: Intel     Published Date: Feb 28, 2019
Keeping the lights on in a manufacturing environment remains top priority for industrial companies. All too often, factories are in a reactive mode, relying on manual inspections that risk downtime because they don’t usually reveal actionable problem data. Find out how the Nexcom Predictive Diagnostic Maintenance (PDM) system enables uninterrupted production during outages by monitoring each unit in the Diesel Uninterrupted Power Supplies (DUPS) system noninvasively. • Using vibration analysis, the system can detect 85% of power supply problems before they do damage or cause failure • Information processing for machine diagnostics is done at the edge, providing real-time alerts on potential issues with ample of lead time for managers to rectify • Graphic user interface offers visual representation and analysis of historical and trending data that is easily consumable
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Intel
Published By: HP - Enterprise     Published Date: Aug 25, 2011
This white paper details how hybrid app security enables organizations to resolve critical security issues faster and cheaper than any other technology
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"application security", cyber-attacks, software security assurance, dast, sast, security breach, data breach, owasp
    
HP - Enterprise
Published By: GFT USA, Inc.     Published Date: Jun 26, 2019
Stream is GFT’s architectural framework on GCP that enables real time processing and analysis of structured and unstructured data using AI and Machine Learning (ML) to extract intelligence from data.
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GFT USA, Inc.
Published By: SAP     Published Date: Jul 18, 2016
People on the frontlines of public-sector fraud management have considerable need to detect, monitor and prevent fraud in real time. They recognize that speed in analysis, detection, investigations and simulations is the key to minimizing taxpayer dollars lost to fraud. Read the report to learn more.
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SAP
Published By: IBM     Published Date: Jul 27, 2016
IBM i2 Enterprise Insight Analysis helps analysts and investigators turn large data sets into comprehensive intelligence, in near real-time. With the help of advanced analytics and visual analysis capabilities, analysts can uncover hidden connections, patterns and trends buried in disparate data. Equip analysts and those on the front line with the tools they need to generate actionable intelligence, with mission critical speed.
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ibm, cyber threat analysis, ibm i2 enterprise insight analysis, cyber security, business intelligence, security, business technology
    
IBM
Published By: Group M_IBM Q119     Published Date: Dec 20, 2018
The security information and event management (SIEM) market is defined by the customer's need to analyze event data in real time for the early detection of targeted attacks and data breaches, and to collect, store, analyze, investigate and report on event data for incident response, forensics and regulatory compliance. The vendors included in our Magic Quadrant analysis have products designed for this purpose, and they actively market and sell these technologies to the security buying center.
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Group M_IBM Q119
Published By: Topsy     Published Date: Jul 16, 2013
Marketing today is real-time, always-on, pervasive, and constant—but following these 5 simple rules guarantees that you’ll stand out from the crowd.
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twitter, advertising, real-time, realtime marketing, real-time marketing, social marketing, social strategy, social listening
    
Topsy
Published By: Visual Factories     Published Date: Mar 15, 2019
Manufacturers are looking for ways to optimize their factory floor and machinery processes to reach their full production potential. Whether it is because of equipment issues or the personnel running the machines, the average OEE machine is running at 60%. With Visual Factories’ plug-and-play cloud-based solution, factory management get enhanced visibility into their manufacturing processes, helping to identify operational inefficiencies and to increase their OEE. Real-time reports for middle management deliver root cause analysis that will increase machine efficiency. Top management use the business insights for maximizing profits and reducing costs. The solution is quick and easy to install and can be set up by on-site maintenance staff. Visual Factories' solution is compatible with any type of production machine in any market segment and has been deployed at metal working and medical tooling plants in the aerospace, automotive and medical industries around the world. Customers incl
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Visual Factories
Published By: Oracle     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle
Published By: BlackLine     Published Date: Jun 12, 2017
In today’s highly complex global business environment, companies are constantly expected to do more with less, to run leaner while becoming more effective than ever. This is especially true for Accounting and Finance. They are now required to not only deliver periodic financial data and reports, but also real-time analysis and intelligence.
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BlackLine
Published By: M86 Security     Published Date: Nov 02, 2010
This white paper examines the Crimeware industry and the Web-based methods currently used to sustain cybercrime.
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m86 security, real-time code analysis, malware threats, cybercrime, anti-virus
    
M86 Security
Published By: Five9     Published Date: Aug 01, 2019
Today’s organizations compete on customer experience and this trend will define the shape and scope of contact centers well into the next decade. To deliver the level of seamless experiences that customers expect, contact centers will need to harness all the advantages technology can offer – specifically, the cloud – to create an “intelligent cloud contact center” that utilizes machine learning and real-time data analysis. So, step one is to move your contact center to the cloud. ASAP. Once you are operating a cloud contact center, the next step is to start leveraging everything this enables you to do. This is where the “Intelligent Cloud Contact Center” comes into play.”
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Five9
Published By: TriGeo Network Security     Published Date: Oct 03, 2008
It’s widely accepted that Security Information and Event Management (SIEM) systems are excellent tools for regulatory compliance, log management and analysis, trouble-shooting and forensic analysis. What’s surprising to many is that this technology can play a significant role in actively defending networks. This whitepaper explains precisely how real-time analysis, combined with in-memory correlation, and automated notification and remediation capabilities can provide unprecedented network visibility, security and control.
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trigeo whitepaper, siem, log management, security event management, automated remediation, active response, correlation, compliance
    
TriGeo Network Security
Published By: M86 Security     Published Date: Feb 09, 2011
This white paper examines the Crimeware industry and the Web-based methods currently used to sustain cybercrime.
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m86 security, real-time code analysis, malware threats, cybercrime, anti-virus
    
M86 Security
Published By: HP     Published Date: Jan 20, 2015
There are many new ways Big Data analytics can significantly boost marketing and promotional efforts through real-time and historical analysis of online data, such as clickstream or purchase transactions. Unstructured data based on social media—even photos and video—offers enormous potential when analyzed with the right tools.
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big data, hp haven, scalable, secure data platform, ecosystem, security
    
HP
Published By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
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evolution, big data, technology, datastax, nosql
    
Datastax
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