real time

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Published By: IBM     Published Date: Oct 06, 2016
Driving competitive advantage with real-time applications, enabled by SAP HANA on IBM Power Systems
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cloud computing, data management, storage solution, power systems, sap, business technology
    
IBM
Published By: SmartFocus     Published Date: Aug 25, 2015
If your marketing isn’t real-time, it’s out of date. Marketing for the moment is now crucial. Real-time interaction management (RTIM) enables marketing messages to change in real-time when they are opened. The latest innovation in digital marketing. Latest independent report reveals the Strong Performers in the RTIM market.
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it management, data management, business technology, data center
    
SmartFocus
Published By: Oracle Corporation     Published Date: May 11, 2012
Learn how organizations can use Oracle Exadata to reduce IT costs through consolidation, manage more data on multiple compression tiers, improve the performance of all applications, and make better business decisions in real time.
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oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications, data management
    
Oracle Corporation
Published By: Oce Business Services     Published Date: Jun 24, 2009
Download this free report to explore the potential of applying business performance management principles to advance document performance management to reduce costs; better manage documents as vital strategic, financial and information assets; and secure positive returns on investments from outsourcing. Learn more today!
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oce, kpi, ekg, document processes, mail center, print/copy operations, records, operations, cost cutting, documents, information, roi, return on investments, oce max, real time, dpm, document intensive, bpm, ediscovery, key performance indicator
    
Oce Business Services
Published By: Darktrace     Published Date: Apr 02, 2019
As organizations increasingly rely on cloud services and SaaS applications to streamline business practices, the familiar paradigm of the network perimeter has dissolved, leaving a porous and ever-changing digital estate in its wake. While the benefits of cloud computing will ensure that migrations continue apace, the unique security challenges presented by the cloud will not only require a more agile mindset, but also self-learning technologies that can move at the speed of cloud deployments and spot subtle deviations indicative of a threat, while providing complete, real-time visibility across the digital business. Darktrace’s world leadership in the field of artificial intelligence for cyber security makes it the most effective and proven solution to detect unprecedented threats and anomalous cyber-incidents in the cloud. Whether faced with an insider threat, an attacker targeting sensitive data in test containers, or a significant misconfiguration that could be exploited in the fut
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Darktrace
Published By: Forcepoint     Published Date: Apr 19, 2016
The longer attackers remain in your network, the more lateral movement is possible and the greater the risk for data theft. Stopping the exfiltration of data, rather than focusing on stopping data breaches, is the most realistic approach to data security and reducing cyber dwell time.
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Forcepoint
Published By: Darktrace     Published Date: Jun 17, 2019
This white paper discusses Darktrace's Industrial Immune System, a fundamental innovation that views data from an Industrial Control System network in real time, and establishes an evolving baseline for what is normal for operators, workstations and automated systems within that environment.
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Darktrace
Published By: Vectra Networks     Published Date: Aug 03, 2015
Learn how Vectra protects Tri-State’s corporate and subscriber data and prevents cyberattacks to the power grid.
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utilities provider, cyberattack detection, vulnerability management, security management, it security, security solution, network breaches, false threats, real-time insights, critical infrastructure, ids, ips
    
Vectra Networks
Published By: B Channels     Published Date: Dec 12, 2019
Security leaders employ a variety of tools and technologies to identify risks and test the effectiveness of their security controls. As a result, security teams are left with point-intime assessments that require them to cobble together data from disparate systems to truly understand the organization’s security posture. This approach is reactive, labor-intensive, and insufficient in scale. In May 2019, Panaseer commissioned Forrester Consulting to evaluate the benefits of automated continuous controls monitoring, a category of solution that provides real-time visibility of assets (e.g., devices, applications, people, data), security controls, and the effectiveness of those controls. Our research found that currently employed technologies don’t provide a complete, real-time view of cybersecurity risk
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B Channels
Published By: BlackBerry Cylance     Published Date: Mar 12, 2019
Today’s advanced cyber threats target every computer and mobile device, including enterprise endpoints, especially those that make up critical infrastructure like industrial control systems and embedded devices that control much of our physical world. The modern computing landscape consists of a complex array of physical, mobile, cloud, and virtual computing, creating a vast attack surface. Meanwhile, the cybersecurity industry is prolific with defense-in-depth security technologies, despite a threat landscape that remains highly dynamic, sophisticated, and automated. Cylance, however, takes a unique and innovative approach of using real-time, mathematical, and machine learning threat analysis to solve this problem at the endpoint for organizations, governments, and end-users worldwide.
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BlackBerry Cylance
Published By: Group M_IBM Q119     Published Date: Feb 25, 2019
The advantages blockchain can bring to the automotive ecosystem, both in facilitating collaboration among participants and enabling capabilities for new mobility business models, have gotten the attention of automotive executives. In addition to enabling a single source of data, blockchain can facilitate device-to-device transactions, smart contracts, and real-time processing and settlement. For the automotive industry, this translates into improvements and operational efficiencies in areas such as supply chain transparency, financial transactions between ecosystem participants, authenticating access to cars, and customer experience and loyalty.
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Group M_IBM Q119
Published By: Group M_IBM Q3'19     Published Date: Jun 24, 2019
The advantages blockchain can bring to the automotive ecosystem, both in facilitating collaboration among participants and enabling capabilities for new mobility business models, have gotten the attention of automotive executives. In addition to enabling a single source of data, blockchain can facilitate device-to-device transactions, smart contracts, and real-time processing and settlement. For the automotive industry, this translates into improvements and operational efficiencies in areas such as supply chain transparency, financial transactions between ecosystem participants, authenticating access to cars, and customer experience and loyalty.
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Group M_IBM Q3'19
Published By: Microsoft     Published Date: Oct 06, 2016
Download the Keystone Research whitepaper to see how top performing enterprises use their IT investments to store, process, and use data to make more effective, real-time decisions. Keystone Research, a global economics and data-driven strategy consulting firm, interviewed senior IT and business decision makers at over three hundred businesses to uncover the relationship between Data & Analytics technologies and business performance. This research shows that companies who have developed the most sophisticated Data & Analytics platforms and apply these capabilities as a regular part of their business enjoy operating margins that are eight percentage points higher than lagging organizations. This translates to $100 million in operating profits on average for the more advanced companies in the sample controlling for factors such as company size and industry vertical.
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microsoft, analytics, data, business impact
    
Microsoft
Published By: Microsoft     Published Date: Feb 02, 2017
Download the Keystone Research whitepaper to see how top performing enterprises use their IT investments to store, process, and use data to make more effective, real-time decisions. Keystone Research, a global economics and data-driven strategy consulting firm, interviewed senior IT and business decision makers at over three hundred businesses to uncover the relationship between Data & Analytics technologies and business performance. This research shows that companies who have developed the most sophisticated Data & Analytics platforms and apply these capabilities as a regular part of their business enjoy operating margins that are eight percentage points higher than lagging organizations. This translates to $100 million in operating profits on average for the more advanced companies in the sample controlling for factors such as company size and industry vertical.
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Microsoft
Published By: Intel     Published Date: Apr 19, 2016
Learn how Intel DCM solution provided an organization real-time and historical data center thermal maps and cooling analysis.
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intel, data center management, power and cooling, power, energy
    
Intel
Published By: SAS     Published Date: Jun 06, 2018
Data integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
Data integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
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SAS
Published By: Informatica     Published Date: Oct 28, 2011
In this White Paper, Bloor Research director Philip Howard discusses how Data Replication can help you deliver active data warehousing for analytics.
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data management
    
Informatica
Published By: McAfee     Published Date: Mar 08, 2013
Databases store companies’ most valuable information assets, but in most cases they’re poorly protected. It’s important to secure databases as well as or better than other systems in the enterprise. But it’s not that simple.
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real-time database monitoring, database authentication, database access control, database activity monitoring, database intrusion prevention, authentication and access control, database security
    
McAfee
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, data management
    
SAS
Published By: SAS     Published Date: Apr 25, 2017
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. The heart and soul of SAS Visual Analytics is the SAS® LASR™ Analytic Server, which ca
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SAS
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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Group M_IBM Q2'19
Published By: StreamSets     Published Date: Dec 05, 2018
Enterprise analytics is quickly evolving into a democratized capability where anyone can access and act on all available information, often in real-time employing advanced techniques. But the complex, dynamic and urgent nature of modern data analytics demands a new approach to data integration. This paper proposes that DataOps, the application of DevOps practices to data analytics, is the best way to overcome these challenges to create an iterative build-operate process for data movement. Read this white paper to: Understand how modern data analytics create data integration challenges due to architectural complexity, operational blindness and data drift. Learn how DevOps pillars of automation and monitoring can create higher developer productivity, operational efficiency and business confidence in data. See specific examples of DataOps functionality being applied to data integration across modern architectures.
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StreamSets
Published By: StreamSets     Published Date: Feb 13, 2019
Enterprise analytics has quickly evolved from a centralized business intelligence function for historical reporting and dashboards to a democratized capability where anyone can access, analyze and act on all available information, often in real-time while employing advanced techniques. But the complex, dynamic and urgent nature of modern data analytics demands a new approach to data integration.
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StreamSets
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