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Published By: Commvault     Published Date: Jul 06, 2016
Think of a wildfire that quickly spreads as it increases in speed and power. That is what is happening today as data growth increases the volume and management complexity of storage, backup and recovery. Now think of trying to stop that fire with a garden hose. Your traditional backup and recovery process is equally under-equipped to manage and facilitate operations that need more speed, efficiency, scalability and reliability to handle today’s 24/7, always-on environment. Here we examine the benefits of moving from a solution comprised of multiple point products to a holistic data protection platform designed to serve today’s enterprise.
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commvault, data protection, storage, backup, recovery, holistic data protection, singe pane of glass, common code base
    
Commvault
Published By: Teradata     Published Date: May 02, 2017
A Great Use of the Cloud: Recent trends in information management see companies shifting their focus to, or entertaining a notion for the first time of a cloud-based solution. In the past, the only clear choice for most organizations has been on-premises data—oftentimes using an appliance-based platform. However, the costs of scale are gnawing away at the notion that this remains the best approach for all or some of a company’s analytical needs. This paper, written by McKnight Consulting analysts William McKnight and Jake Dolezal, describes two organizations with mature enterprise data warehouse capabilities, that have pivoted components of their architecture to accommodate the cloud.
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data projects, data volume, business data, cloud security, data storage, data management, cloud privacy, encryption
    
Teradata
Published By: SWsoft     Published Date: Aug 21, 2009
Today's IT organizations are dealing with the consequences of exploring IT Infrastructure growth and complexity. With its growing complexity and volume, the cost of managing the infrastructure from simple patch management to skill sets requirements for IT administrators is increasing.
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active directory, bandwidth management, convergence, swsoft, server virtualization, patch management, network management, infrastructure
    
SWsoft
Published By: Red Hat, Inc.     Published Date: Jul 12, 2012
Recently, enterprises have seen enormous gains in scalability, flexibility, and affordability as they migrated from proprietary, monolithic server architectures to architectures that are virtualized, open source, standardized, and commoditized.
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scalability, flexibility, affordability, performance, ease-of-use, reduced acqisition costs, reduced maintenance costs, red hat storage server
    
Red Hat, Inc.
Published By: IBM     Published Date: Jan 02, 2014
This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
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ibm, analytics, global business service, big data, business value, it professionals, volume, velocity
    
IBM
Published By: IBM     Published Date: Mar 05, 2014
For many years, companies have been building data warehouses to analyze business activity and produce insights for decision makers to act on to improve business performance. These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse. Typically, a history of business activity is built up over a number of years allowing organizations to use business intelligence (BI) tools to analyze, compare and report on business performance over time. In addition, subsets of this data are often extracted from data warehouses into data marts that have been optimized for more detailed multi-dimensional analysis.
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ibm, big data, data, big data platform, analytics, data sources, data complexity, data volume
    
IBM
Published By: Esker     Published Date: Jul 15, 2013
Whether the number is a minority or a majority of total sales order volume, fax often represents the bulk of a company’s order management expenses. Fax orders typically require a separate processing environment made up of fax machines or, preferably, fax server software to capture orders and distribute them among CSRs who enter the information into ERP applications.
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order processing, sales order processing, sales orders, order management order automation, edi, customer service, fax orders, email orders
    
Esker
Published By: Neustar Inc.     Published Date: Oct 14, 2013
As the digital universe evolves in both volume and scope, companies must be diligent about protecting their content. Fortunately, companies can easily leverage IP information to protect themselves. This paper explores the best practices of using IP intelligence for digital rights management to reduce risk to online content.
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digital rights management, ip intelligence, best practices, neutar, security, wireless security, online content, rights
    
Neustar Inc.
Published By: TIBCO     Published Date: May 15, 2013
According to Forrester, most organizations today are only using 12% of their available data and only 37% of organizations are planning some type of big data technology project. At a time when companies are seeing volume of information increase quickly, it’s time to take a step back and look at the impact of big data. Join Mike Gualtieri, Principal Analyst at Forrester, for this webcast exploring the importance of integration in your big data initiatives. Discover how your ability to operate, make decisions, reduce risks and serve customers is inextricably linked to how well you’re able to handle your big data. Continue on to gain insight into: •3 key big data management activities you need to consider •Technologies you need to create for your big data ecosystem •A multi-dimensional view of the customer is the holy grail of individualization •Overcoming key integration challenges And more!
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big data, integration, architecture, database, data warehousing, operations management
    
TIBCO
Published By: AWS     Published Date: Oct 26, 2018
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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data, lake, amazon, web, services, aws
    
AWS
Published By: AWS     Published Date: Nov 02, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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AWS
Published By: Amazon Web Services     Published Date: Oct 09, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyse data that addresses many of these challenges. Data Lakes allow an organization to store all of their data, structured and unstructured, in one, centralized repository.
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cost effective, data storage, data collection, security, compliance, platform, big data, it resources
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: VMware AirWatch     Published Date: Feb 21, 2017
By implementing the VMware App Volumes™ application management solution, OGL built a multitenant VDI environment that delivers an extensive range of applications to customers in real time, with full application functionality on any device, while also reducing OpEx and CapEx. Download this case study to learn how OGL Computer addressed these issues and more with VMware App Volumes: • Scale VDI service for more customers and applications. • Reduce expenses of Citrix VDI solution delivery. • Deliver and manage applications dynamically, in real time. • Give users desktop access on any Internet-connected device.
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VMware AirWatch
Published By: Sanbolic     Published Date: Dec 03, 2007
Clustered volume manager enables administrators to centrally configure and assign storage assets in a SAN storage environment in Microsoft System Management Server 2003 and Microsoft Operations Manager 2005 environments.
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windows, storage, san, nas, sanbolic
    
Sanbolic
Published By: Numara Software     Published Date: Jul 09, 2009
In this informative webinar, you will learn about the challenges of implementing configuration management along with suggestions on how to get started, and best practices to ensure success. You will also learn how Numara® FootPrints® Configuration Management, with its fast implementation, practical approach to implementing configuration management and automated integration to auto-discovery tools, takes the pain and time out of creating and maintaining a functional CMDB. Learn more today!
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configuration management, cmdb, numara, footprints, auto-discovery tools, hardware, itil, service management
    
Numara Software
Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: SAS     Published Date: Mar 06, 2018
As your organization struggles with growing volumes and sources of data, increasingly complex regulatory requirements, and pressure to do more with fewer resources, SAS Data Management can help. How? Our solution helps you make sense of your data so you can make better decisions. Then you can take the right actions to improve customer experience, boost revenue, become more efficient and remain compliant
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SAS
Published By: Adobe     Published Date: Oct 06, 2015
The sheer volume of data available to marketers can be daunting, especially without a data management platform (DMP). With a DMP, marketers can handle growing data challenges, create powerful customer insights and deliver marketing campaigns that increase revenue.
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adobe, digital advertising, social, brand, dmp, digital media platform
    
Adobe
Published By: Adobe     Published Date: Feb 08, 2016
The sheer volume of data available to marketers can be daunting, especially without a data management platform (DMP). With a DMP, marketers can handle growing data challenges, create powerful customer insights and deliver marketing campaigns that increase revenue.
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adobe, marketing, data, dmp, data management, customer insights, roi
    
Adobe
Published By: VMware AirWatch     Published Date: Sep 21, 2016
Deliver better services, reduce expenses and comply with regulations are familiar business demands heard by financial services IT leaders. Simultaneously, the time and cost of managing custom apps to run core business operations continues to rise. Not only does this obstruct the speed of innovation adoption, it also increases the need for better end user experiences due to app management volume. How can financial services IT teams enable more efficacy alongside business growth, while reducing their own IT management burden? This ebook examines four ways financial services organizations can deliver apps and manage users at scale while reducing costs and optimizing existing investments.
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VMware AirWatch
Published By: Group M_IBM Q2'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q2'19
Published By: Group M_IBM Q3'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Group M_IBM Q3'19     Published Date: Sep 04, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Altiscale     Published Date: Oct 19, 2015
In this age of Big Data, enterprises are creating and acquiring more data than ever before. To handle the volume, variety, and velocity requirements associated with Big Data, Apache Hadoop and its thriving ecosystem of engines and tools have created a platform for the next generation of data management, operating at a scale that traditional data warehouses cannot match.
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big data, analytics, nexgen, hadoop, apache
    
Altiscale
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