data strategy

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Published By: Greenhouse     Published Date: Jan 25, 2017
The Structured Hiring method ensures an effective and unbiased recruiting process. Get your free guide today.
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recruiting tips, recruiting software, recruiting strategy, applicant tracking, talent acquisition, recruiting metrics, recruiting data, talent metrics, candidate experience, candidate sourcing, candidate management, talent strategy, recruiting, recruitment
    
Greenhouse
Published By: Eaton     Published Date: Jan 26, 2016
This white paper explains why many data centers are ill-equipped to support today’s most important new technologies; discusses why packaged power and cooling solutions can be a flawed way to upgrade existing facilities; and describes the core components of a data center upgrade strategy capable of enhancing efficiency and power density more completely and cost-effectively.
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eaton, modern data centers, data center solutions, virtualization, big data, converged infrastructures, it management, knowledge management, enterprise applications
    
Eaton
Published By: Eaton     Published Date: Jan 26, 2016
When designing a power protection scheme for their data center, IT and facilities managers must ask themselves whether a distributed or centralized backup strategy makes more sense. Unfortunately, there is no easy answer to that question. Companies must weigh each architecture’s advantages and disadvantages against their financial constraints, availability needs and management capabilities before deciding which one to employ. This white paper will simplify the decision-making process and lessen the potential weaknesses of whichever strategy you ultimately select.
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eaton, distributed backup strategy, centralized backup strategy, facility managers, data center solutions, it management, knowledge management, enterprise applications
    
Eaton
Published By: IBM     Published Date: May 28, 2014
The ability to keep pace with trends like big data, open data, sophisticated analytics, and the de-compartmentalization of data silos and processes, distinguishes leading master data management (MDM) solutions from their counterparts. IBM, one of the five vendors in this evaluation, is positioned as THE leader with the most prominent, widely implemented solution in the market.
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ibm, forrester, master data management, big data, database management technology, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, data persistence, virtualize data, lifecycle management, big data strategy, it management, data management, data center
    
IBM
Published By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
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ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, lifecycle management
    
IBM
Published By: IBM     Published Date: Apr 23, 2015
With IBM analytics for big data with a smart mobile strategy, banks can increase wallet share and assets under management while lowering the organization’s operating ratio by using more efficient channels.
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ibm, analytics, efficiencies, digital banking, management, strategy, data management, business technology, data center
    
IBM
Published By: IBM     Published Date: Aug 28, 2014
Not storing data is cheaper than storing it. As enterprise data continues to grow and IT budgets remain flat, organizations need to more effectively maximize existing storage capacity and manage storage spend based on data value. In this white paper, Enterprise Strategy Group Sr. Analyst Mark Peters demonstrates how IBM's Information Lifecycle Governance solutions can help IT buyers improve the information economics for their organizations by curtailing data growth through defensible disposal of data.
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data storage, data value, ilg, data disposal, data management
    
IBM
Published By: IBM     Published Date: Oct 22, 2014
A case study on how a major oil and gas producer saves 35 percent on data storage costs and 30 percent in litigation-related costs by adopting a smarter data discovery and defensible disposal strategy, using IBM Enterprise Content Management solutions.
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legacy data, data storage costs, data storage, content management, it management, knowledge management, data management
    
IBM
Published By: IBM     Published Date: Oct 22, 2014
Not storing data is cheaper than storing it. As enterprise data continues to grow and IT budgets remain flat, organizations need to more effectively maximize existing storage capacity and manage storage spend based on data value. In this white paper, Enterprise Strategy Group Sr. Analyst Mark Peters demonstrates how IBM's Information Lifecycle Governance solutions can help IT buyers improve the information economics for their organizations by curtailing data growth through defensible disposal of data.
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data storage, big data, data disposal, data value, it management, data management
    
IBM
Published By: IBM MaaS360     Published Date: Oct 08, 2015
Security is really about access; today’s work demands access to anything from anywhere on any device. Learn how to securely let employees share, edit and distribute work data across iOS, Android and Windows.
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ibm, fiberlink, data security, mobile, mobile strategy, networking, wireless, enterprise applications, data management, business technology
    
IBM MaaS360
Published By: IBM     Published Date: Jan 05, 2015
As the number of connected devices grows from billions to hundreds of billions, and as governments and corporations race to take control of devices and data, we need to save the Internet of Things (IoT). Successfully scaling the IoT means executives must rethink the technology strategy.
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it strategy, modern computing, iot, cost of computing, it management, knowledge management, enterprise applications, data management
    
IBM
Published By: IBM     Published Date: Apr 09, 2015
This ebook outlines four steps to develop a proactive approach to data security and privacy that will help you keep big data safe, and shows how IBM InfoSphere solutions can help protect data while giving your staff the right levels of access to do their jobs efficiently and accurately.
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data security, ibm, ibm infosphere, privacy strategy, big data security, security, it management, knowledge management, data management
    
IBM
Published By: IBM     Published Date: Jul 15, 2015
This ebook outlines four steps to develop a proactive approach to data security and privacy that will help you keep big data safe
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big data security, data privacy, data protection, sensitive data, data risk management, vulnerability management, ibm solutions, data breaches, compliance
    
IBM
Published By: IBM     Published Date: Oct 02, 2015
This ebook outlines four steps to develop a proactive approach to data security and privacy that will help you keep big data safe, and shows how IBM InfoSphere solutions can help protect data while giving your staff the right levels of access to do their jobs efficiently and accurately.
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ibm, big data, data security, privacy strategies, ibm infosphere, security, it management, knowledge management, business technology
    
IBM
Published By: IBM     Published Date: Jul 12, 2016
Join us for a complimentary webinar with Mark Simmonds, IBM big data IT Architect who will talk with leading analyst Mike Ferguson of Intelligent Business Strategies about the current fraud landscape. They will discuss the business impact of fraud, how to develop a fraud-protection strategy and how IBM z Systems analytics solutions and predictive models can dramatically reduce your risk exposure and loss from fraud.
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ibm, z systems, fraud loss reduction, fraud management, fraud prevention, fraud analytics, roi, security
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
This infographic explains how to build your big data strategy on a solid foundation.
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ibm, analytics, big data, strategy, software development, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Oct 21, 2016
By next year over half of all US companies will formally support BYOD, bringing on the challenge of securing data and applications on devices that may often be in the hands malicious users, or worse – teenagers looking to win a game of Pokémon Go with mom’s work iPhone. And, thanks to the consumerization of IT, mobile users increasingly expect the same smooth user experience with business applications that is provided by popular games and consumer applications. Fortunately, increased mobility and the bring your own device explosion don’t always add up to increased security challenges and UI/UX struggles. This Tech Byte series will look at the most important considerations when planning a mobile strategy – from application development platform to security and governance to user interface guidelines, and present best practices that businesses of all kinds can use to help ensure a successful shift towards a mobile-first enterprise.
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ibm, mobile, mobile security, devices, platform to device, networking, enterprise applications
    
IBM
Published By: IBM     Published Date: Oct 21, 2016
By next year over half of all US companies will formally support BYOD, bringing on the challenge of securing data and applications on devices that may often be in the hands malicious users, or worse – teenagers looking to win a game of Pokémon Go with mom’s work iPhone. And, thanks to the consumerization of IT, mobile users increasingly expect the same smooth user experience with business applications that is provided by popular games and consumer applications. Fortunately, increased mobility and the bring your own device explosion don’t always add up to increased security challenges and UI/UX struggles. This Tech Byte series will look at the most important considerations when planning a mobile strategy – from application development platform to security and governance to user interface guidelines, and present best practices that businesses of all kinds can use to help ensure a successful shift towards a mobile-first enterprise.
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ibm, cloud, mobility, enterprise, mobile applications, mobile application strategy, networking, enterprise applications
    
IBM
Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy. IDC believes that this emerging environment is to date still highly undefined, even as businesses must make critical decisions. Should businesses develop in-house or use VARs, systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some hybrid form? Can they use existing infrastructure, or do AI applications and deep learning require new servers with new capabilities? We believe that many of these questions can be
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Group M_IBM Q418
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
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Group M_IBM Q2'19
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