variety data

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Published By: Dell     Published Date: Sep 17, 2014
As the 3 V’s of big data: volume, velocity and variety continue to grow, so too does the opportunity for finance sector firms to capitalize on this data for strategic advantage. Read how.
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dell, finance data, data storage, financial records, secure finance, cloud, finance cloud
    
Dell
Published By: Dell     Published Date: Aug 24, 2015
This paper discusses how the many Dell | Cloudera Hadoop solutions help organizations of all sizes, and with a variety of needs and use cases, tackle their big data requirements.
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dell, big data, data management, cloud solutions, hadoop, servers, cloud computing, storage
    
Dell
Published By: Marketo     Published Date: Feb 07, 2017
Read this complimentary copy of the Gartner Magic Quadrant for Digital Marketing Hubs, and find out why Marketo was named a leader based on completeness of vision and the ability to execute. As a digital marketing hub, Marketo allows marketers to think beyond email campaigns and address customers personally and consistently as individuals through a variety of contexts and formats. Digital marketing hubs, like Marketo, unify disparate marketing data and processes to drive acquisition, engagement, conversion and transaction across complex customer journeys. The full report includes: Market evaluation and analysis of 22 vendors Insights for selecting a vendor based on your organization's requirements Opportunities and challenges faced when deploying digital marketing hubs Download the report to learn about these topics and more.
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digital marketing hub, email campaigns, customers, disparate marketing data, vendor selection, gartner
    
Marketo
Published By: Asentria Corporation     Published Date: Sep 04, 2007
More than ever before, IT managers need to secure equipment and facilities against a variety of intrusive conditions that could cripple critical operations, resulting in system malfunctions, loss of data or intellectual property, damage to mission critical hardware or even theft of valuable physical assets. Such conditions often include environmental events, failure of air conditioning systems, power outages, and untoward human actions.
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telecom alarms, snmp traps, remote site managers, terminal servers, remote access, snmp monitoring, snmp, contact closures, fault management, network management, remote site monitoring, remote site alarms, environmental monitoring, network alarm monitoring, network alarm management, remote telemetry units, alarm management system, network management systems, network monitoring, protocol mediation
    
Asentria Corporation
Published By: ElcomSoft     Published Date: Dec 06, 2007
In order to protect important data, we use a large variety of methods and technologies, especially when the data in question is confidential and essential for day-to-day operations of a business and for making important management decisions. "If you have the information, you own the world" has become the basic tenet of our times, where control over data is of the utmost significance. The loss of access to important data can have a very negative impact on the company’s business.
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password, password management, access control, server access, network management, windows, windows management, user access, data protection, elcomsoft
    
ElcomSoft
Published By: IBM     Published Date: Aug 06, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media
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ibm, insurance, data, big data, analytics, solutions
    
IBM
Published By: HP     Published Date: Apr 13, 2014
With growth in the volume and variety of data needed to monitor and manage complex IT systems, IT leaders have had to acquire new technologies to manage this data. This will require that a single, architected platform be procured to improve root-cause analysis and short-term predictive analysis.
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ops analytics, operations analytics, gartner, big data, analytics, predictive analytics, bsm, business service management
    
HP
Published By: HP     Published Date: Apr 23, 2014
With growth in the volume and variety of data needed to monitor and manage complex IT systems, IT leaders have had to acquire new technologies to manage this data. This will require that a single, architected platform be procured to improve root-cause analysis and short-term predictive analysis.
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ops analytics, operations analytics, gartner, big data, analytics, predictive analytics, bsm, business service management
    
HP
Published By: IBM     Published Date: Oct 13, 2016
In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. Download this white paper to learn how.
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database, big data, analytics, infrastructure
    
IBM
Published By: IBM     Published Date: Mar 30, 2017
To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize its value, and integrate it at a more granular level than ever before—focusing on the individual transaction level, rather than on general summary data. As data volumes continue to explode, clients must take advantage of a fully scalable information integration architecture that supports any type of data integration technique such as extract, transfer and load (ETL), data replication or data virtualization.
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data integration, data security, data optimization, data virtualization, database security
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: IBM     Published Date: Jul 09, 2018
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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IBM
Published By: Tenable     Published Date: Feb 07, 2018
"This IDC Technology Spotlight examines the evolution of vulnerability management. By leveraging the cloud and new technologies that deliver greater visibility, organizations can gain an accurate picture of their assets and overall risk posture. This is a critical step toward addressing the current landscape where attackers are using a wide variety of vectors such as mobile, social, and cloud-based attacks to infiltrate organizations and steal data. By reading this report you will get an overview of: - Benefits of cloud-based security and vulnerability management - Challenges of adopting cloud-based vulnerability management - IDC assessment of Tenable.io cloud vulnerability management"
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Tenable
Published By: Group M_IBM Q2'19     Published Date: Jul 01, 2019
The days of data being narrowly defined as highly structured information from a few specific sources is long gone. Replacing that notion is the reality of a wide variety of data types coming from multiple sources, internal and external, to an organization. All of it is in service of providing everyone from IT, to line-of-business (LOB) employees, to C-level executives with insights that can have an immediate and transformative impact.
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Group M_IBM Q2'19
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
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