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Published By: IBM     Published Date: Apr 18, 2016
"Five high-value uses for big data: IBM has conducted surveys, studied analysts’ findings, talked with more than 300 customers and prospects and implemented hundreds of big data solutions. As a result, it has identified five high-value use cases that enable organizations to gain new value from big data."
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ibm, mdm, big data, trusted data, data solutions, data management
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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ibm, mdm, big data, data management, data matching, customer analytics
    
IBM
Published By: IBM     Published Date: Jul 15, 2016
As big data environments ingest more data, organizations will face significant risks and threats to the repositories containing this data. Failure to balance data security and quality reduces confidence in decision making. Read this e-Book for tips on securing big data environments.
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ibm, data, security, big data, data management
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
Data movement and management is a major pain point for organizations operating HPC environments. Whether you are deploying a single cluster, or managing a diverse research facility, you should be taking a data centric approach. As data volumes grow and the cost of compute drops, managing data consumes more of the HPC budget and computational time. The need for Data Centric HPC architectures grows dramatically as research teams pool their resources to purchase more resources and improve overall utilization. Learn more in this white paper about the key considerations when expanding from traditional compute-centric to data-centric HPC.
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ibm, analytics, hpc, big data, software development, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Sep 30, 2016
"The malware industry supplies all the components cybercriminals need to easily perpetrate malware-driven financial fraud and data theft. In today’s virtual world, the scope of organizations vulnerable to malware-driven cybercrime is quite broad. In addition to banks and credit unions that are subject to online banking fraud, financial fraud can be perpetrated on insurance companies, payment services, large e-commerce companies, airlines and many others. "
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ibm, security, web fraud, malware, cybercrime, cyber security, knowledge management, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance, knowledge management, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
The worldwide growth rate of digital data is staggering. If you're a CIO or a data center administrator, data growth statistics aren't just big numbers, they are a big problem -- for your company. Email messages, social media and blog posts, text and instant messages, photos, video and audio, machine-generated data, and transactional detail are on track to overwhelm your storage capacity. Read this paper for practical advice and smarter solutions for managing the information in your organization and getting back to a position of mastery over your data. Get this valuable resource now.
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ibm, analytics, big data, information governance, ecm, information lifecycle governance, knowledge management, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: Jan 09, 2017
As security threats increase and government regulations require more control over users and data, it is important for organizations to evolve their security measures. By aligning governance related policies and rules with all identity management processes, organizations can achieve continuous, sustainable compliance, thereby reducing the need for after the fact fixes and expensive, error prone manual remediation. IBM Security Identity Governance and Intelligence helps organizations effectively, comprehensively manage identities and application access
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ibm, security, identity governance and intelligence, identity governance, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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customer analytics, data analysis, competitive advantage, understanding your customer base
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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cloud-based data, data quality, data management, hybrid environment, decision making
    
IBM
Published By: IBM     Published Date: Jul 17, 2018
Ensuring your data is compliant can be a fairly straightforward task. Your IT team works their way through the checklist, and stays out of trouble with lawyers and regulatory agencies. There’s value to that. But true data protection is more than regulatory compliance. In fact, even if you’re compliant, your organization could still be at risk unless you strategically identify and protect your most valuable data. Traditionally, you’ve been presented with IT security metrics—sometimes reassuring, other times alarming. But simply reviewing IT security metrics is not meaningful in and of itself. As an executive, you don’t evaluate issues in siloes. Instead, you excel at assessing issues in the broader context of your organizational operations. In other words, technical security data and metrics lack value unless viewed through the lens of business risk. When you’re presented with IT security metrics, your question is: What does this mean for my business? And ultimately, what data should I
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IBM
Published By: IBM     Published Date: Jul 17, 2018
As of May 25, 2018, organizations around the world—not just those based in the EU—need to be prepared to meet the requirements outlined within the EU General Data Protection Regulation (GDPR). Those requirements apply to any organization doing business with any of the more than 700 million EU residents, whether or not it has a physical presence in the EU. IBM® Security can help your organization secure and protect personal data with a holistic GDPR-focused Framework that includes software, services and GDPR-specific tools. With deep industry expertise, established delivery models and key insights gained from helping organizations like yours navigate complex regulatory environments, IBM is well positioned to help you assess your needs, identify your challenges and get your GDPR program up and running
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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 Q418     Published Date: Sep 10, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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Group M_IBM Q418
Published By: Group M_IBM Q418     Published Date: Sep 25, 2018
As of May 25, 2018, organizations around the world—not just those based in the EU—need to be prepared to meet the requirements outlined within the EU General Data Protection Regulation (GDPR). Those requirements apply to any organization doing business with any of the more than 700 million EU residents, whether or not it has a physical presence in the EU. IBM® Security can help your organization secure and protect personal data with a holistic GDPR-focused Framework that includes software, services and GDPR-specific tools. With deep industry expertise, established delivery models and key insights gained from helping organizations like yours navigate complex regulatory environments, IBM is well positioned to help you assess your needs, identify your challenges and get your GDPR program up and running.
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Group M_IBM Q418
Published By: Group M_IBM Q418     Published Date: Sep 25, 2018
There’s no getting around it. Passed in May 2016, the European Union (EU) General Data Protection Regulation (GDPR) replaces the minimum standards of the Data Protection Directive, a 21-year-old system that allowed the 28 EU member states to set their own data privacy and security rules relating to the information of EU subjects. Under the earlier directive, the force and power of the laws varied across the continent. Not so after GDPR went into effect May 25, 2018. Under GDPR, organizations are subject to new, uniform data protection requirements—or could potentially face hefty fines. So what factors played into GDPR’s passage? • Changes in users and data. The number, types and actions of users are constantly increasing. The same is true with data. The types and amount of information organizations collect and store is skyrocketing. Critical information should be protected, but often it’s unknown where the data resides, who can access it, when they can access it or what happens once
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Group M_IBM Q418
Published By: Cisco     Published Date: Jul 11, 2016
Though IP telephony has been available commercially since the mid ‘90s, it remains an emerging technology for many organizations. Only about 28% of companies have moved all endpoints (handsets, softphones, audio bridges) to IP, according to Nemertes’ research data. The rest of organizations are either in the process of migrating fully to IP, stuck in a hybrid rollout requiring them to manage typically multiple TDM and IP providers, or firmly planted in TDM. This report reviews the issues and benefits associated with moving to an all-IP environment, based on interviews with IT professionals who have moved to all IP or are in the process of doing so.
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Cisco
Published By: Cisco     Published Date: Jul 11, 2016
Operational efficiency and cost savings. Datadriven business insights. Organizational agility and market differentiation. Enterprises in every industry are pursuing such gains, but they cannot be achieved with a fragmented, siloed technology infrastructure. Technological integration doesn’t happen overnight, of course. It takes years of behind-the-scenes teamwork and engineering—backed by decades of expertise, research, and development—to have a broad and lasting impact. This special edition of Unleashing IT highlights the fruits of those labors, showcasing the unparalleled alignment of Microsoft, Cisco, and Intel technologies. In the following pages, you’ll read about the advancement and unique value of integrated solutions, spanning cloud environments, data centers, and management tools. You’ll also hear from organizations that are aking advantage of these converged technologies, including King County, Provincia Net, and Swinburne University.
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Cisco
Published By: Cisco     Published Date: Jul 11, 2016
Digitization is reshaping the business landscape at an unprecedented rate. The disruption of established businesses used to take decades, but natively digital organizations such as Uber, Google and Amazon have disrupted their respective markets in fewer than 10 years. Digital transformation is creating new winners and losers faster than ever before. Exhibit 1 shows that in 1960, on average, businesses remained on the S&P 500 Index for 50 to 60 years; by 1980, the rate of change was cut in half. Based on these trends, by 2025, businesses are forecast to stay on the index for an average of only 12 years. Leveraging this economic data, ZK Research predicts that 75% of the index will turn over in the next 10 years. New market leaders will emerge, and established organizations will struggle to survive.
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Cisco
Published By: Cisco     Published Date: Jul 11, 2016
In June 2013, Cisco commissioned Forrester Consulting to examine the total economic impact and potential return on investment (ROI) enterprises may realize by deploying the CIsco Secure Data Center Solution. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of the Cisco Secure Data Center Solution on their organizations.
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Cisco
Published By: IBM     Published Date: Apr 03, 2017
Businesses today certainly do not suffer from a lack of data. Every day, they capture and consume massive amounts of information that they use to make strategic and tactical decisions. Yet organizations often lack two critical capabilities when it comes to making the right decisions for the business: the ability to make accurate predictions about the future, and to then use those predicted insights in conjunction with organizational goals to identify the best possible actions they should take. The combination of predictive analytics and decision optimization provides organizations with the ability to turn insight into action. Predictive analytics offers insights into likely scenarios by analyzing trends, patterns and relationships in data. Decision optimization prescribes best-action recommendations given an organization’s business goals and business dynamics, taking into account any tradeoffs or consequences associated with those actions.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources, data optimization
    
IBM
Published By: IBM     Published Date: Apr 03, 2017
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins. Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses. Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources
    
IBM
Published By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: IBM     Published Date: Apr 20, 2017
The growth of virtualization has fundamentally changed the data center and raised numerous questions about data security and privacy. In fact, security concerns are the largest barrier to cloud adoption. Read this e-Book and learn how to protect sensitive data and demonstrate compliance. Virtualization is the creation of a logical rather than an actual physical version of something. such as a storage device, hardware platform, operating system, database or network resource. The usual goal of virtualization is to centralize administrative tasks while improving resilience, scalability and performance and lowering costs. Virtualization is part of an overall trend in enterprise IT towards autonomic computing, a scenario in which the IT environment will be able to manage itself based on an activity or set of activities. This means organizations use or pay for computing resources only as they need them.
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data protection, data security, data optimization, organization optimization, cloud management, virtualization, data center, cloud environment
    
IBM
Published By: IBM     Published Date: Apr 20, 2017
An interactive white paper describing how to get smart about insider threat prevention - including how to guard against privileged user breaches, stop data breaches before they take hold, and take advantage of global threat intelligence and third-party collaboration. Security breaches are all over the news, and it can be easy to think that all the enemies are outside your organization. But the harsh reality is that more than half of all attacks are caused by either malicious insiders or inadvertent actors.1 In other words, the attacks are instigated by people you’d be likely to trust. And the threats can result in significant financial or reputational losses.
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insider threats, data management, organization management, data analytics, threat detection, risk management, fraud discovery, forensics investigation, incident response
    
IBM
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