data organization

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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
Published By: IBM     Published Date: May 01, 2017
Today's mobile landscape is very much a moving target. IT managers must keep track of all types of devices and platforms, hundreds if not thousands of applications and a threat landscape that changes by the minute. In this ever-changing environment, IT staff often find themselves drowning in mobile minutiae, overwhelmed by mountains of endpoint data but unable to extract meaning from it or make business decisions based on it. The tactical challenge of keeping infrastructure and business data secure while keeping workers productive each day takes precedence. And even then, IT managers can find themselves choosing between security and productivity as they decide how best to spend limited time and resources. This whitepaper will guide you how to get deep visibility into relevant endpoint data within the platform, granting actionable intelligence that can have a measurable impact on your organization.
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it staff, applications, business data, data security, it managers, endpoint data, device, platforms
    
IBM
Published By: IBM     Published Date: Jun 21, 2017
NoSQL databases and Apache Spark are a potent combination for rapid integration, transformation and analysis of all kinds of business data. With its data syncing and analytics capabilities, IBM Cloudant offers unique advantages as a NoSQL database for many Spark use cases. IT decision-makers, data scientists and developers need to know how and when to apply these technologies most effectively. IBM can offer a host of resources and tools to help your organization gain value from Cloudant and Spark quickly, and with minimal up-front investment.
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ibm, ibm cloudant, apache spark, nosql, database
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
IBM Security and Ponemon Institute are pleased to present the 2017 Cost of Data Breach Study: United States, our 12th annual benchmark study on the cost of data breach incidents for companies located in the United States. The average cost for each lost or stolen record containing sensitive and confidential information increased from $221 to $225. The average total cost experienced by organizations over the past year increased from $7.01 million to $7.35 million. To date, 572 U.S. organizations have participated in the benchmarking process since the inception of this research.
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data breach, data protection, trends, research study, information protection
    
IBM
Published By: IBM     Published Date: Oct 03, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business.
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data, enterprise resource planning, customer relationship management, business intelligence, data management systems
    
IBM
Published By: IBM     Published Date: Oct 13, 2017
IBM Security offers one of the most advanced and integrated portfolios of enterprise security products and services. The portfolio, supported by world-renowned X-Force research, provides security intelligence to help organizations holistically protect their infrastructures, data and applications, offering solutions for identity and access management, database security, application development, risk management, endpoint management, network security and more. These solutions enable organizations to effectively manage risk and implement integrated security for mobile, cloud, social media and other enterprise business architectures. IBM operates one of the world’s broadest security research, development and delivery organizations, monitors 15 billion security events per day in more than 130 countries, and holds more than 3,000 security patents.
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it security, malware, malware protection, virus prevention, ibm, threat intelligence
    
IBM
Published By: IBM     Published Date: Oct 16, 2017
Data—dynamic, in demand and distributed—is challenging to secure. But you need to protect sensitive data, whether it’s stored on-premises, off-site, or in big-data, private- or hybrid-cloud environments. Protecting sensitive data can take many forms, but nearly any organization needs to keep its data accessible, protect data from loss or compromise, and comply with a raft of regulations and mandates. These can include the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act of 1996 (HIPAA) and the European Union (EU) General Data Protection Regulation (GDPR). Even in the cloud, where you may have less immediate control, you must still control your sensitive data—and compliance mandates still apply.
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ibm, encryption, hybrid-cloud, data protection
    
IBM
Published By: IBM     Published Date: Oct 16, 2017
When you’re presented with IT security metrics, your question is: What does this mean for my business? And ultimately, what data should I be most concerned with? The point is, not all data deserves equal protection. A more effective approach is to understand: • Which data is most critical (also known as “crown jewels”)? • Where does that data reside? • How is it exposed to security risks? • What potential impact would a security breach to this data have on your organization? • What are the appropriate steps to take based on the data’s criticality?
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ibm, data, it security, data analytics
    
IBM
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
"Businesses understand more than ever that they depend on data for insight and competitive advantage. And when it comes to data, they have always wanted easy access and fast performance. But how is the situation different now? Today, organizations want those elements and more. They want IT to strip away the limitations of time with faster deployment of new databases and applications. They want IT to reduce the limitations of distance by giving remote and branch offices better and more reliable access. And in a global world where business never stops, they want IT to ensure data availability around the clock. If IT can deliver databases and applications faster, on a more automated and consistent basis, to more locations without having to commit onsite resources, IT will be free to focus on more strategic projects."
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Oracle PaaS/IaaS/Hardware
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
Listen as Oracle Executive Vice President of Converged Infrastructure Dave Donatelli announces the expansion of the Oracle Database Appliance portfolio, and explains how Oracle can provide organizations with a pathway to the cloud. Discover how your organization can reduce database complexity, simplify database administration, and better control costs.
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Oracle PaaS/IaaS/Hardware
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
Oracle’s latest Database Cloud release offers game changing enterprise cloud scale capabilities that are designed to help organizations of any size from enterprise, to SMBs including individual developers easily onboard to the cloud.
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Oracle PaaS/IaaS/Hardware
Published By: Seagate Technology     Published Date: May 15, 2015
Server virtualization, the cloud, and big data are all combining to force changes at the storage layer so that IT organizations can deliver improved strategic value to the organization.
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storage, cloud, server virtualization, it ecosystem, big data
    
Seagate Technology
Published By: SWsoft     Published Date: Aug 08, 2007
As virtualization becomes more pervasive in the datacenter, organizations are deploying complementary types of virtualization technologies. Read this white paper to learn how blending application and OS virtualization using Citrix and Virtuozzo will provide stronger and more robust virtualization solution.
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os virtualization, virtualization, citrix, best practices, swsoft, sw soft, application virtualization, server virtualization, network management, paravirtualization
    
SWsoft
Published By: Utimaco     Published Date: Aug 18, 2008
Data protection programs at most organizations are concerned with protecting sensitive data from external malicious attacks, relying on technical controls that include perimeter security, network/wireless surveillance and monitoring, application and point security management, and user awareness and education. In this paper, the different leakage points are mapped with regulations and best practices.
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leak, leakage, data protection, pci, cardholder, cardholder data, utimaco, database security, security
    
Utimaco
Published By: SAS     Published Date: Jun 05, 2017
Data professionals now have the freedom to create, experiment, test and deploy different methods easily – using whatever skill set they have – all within one cohesive analytics platform. IT leaders gain the ability to centrally manage the entire analytics life cycle for both SAS and other assets with one environment. Organizations get faster results and better ROI from analytics efforts.
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SAS
Published By: SAS     Published Date: Aug 13, 2018
You may know some data management basics, but are you aware of the transformational results that can result from doing data management right? This paper explains core data management capabilities, then describes how a solid data management foundation can help you get more out of your data. Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
Despite heavy, long-term investments in data management, data problems at many organizations continue to grow. One reason is that data has traditionally been perceived as just one aspect of a technology project; it has not been treated as a corporate asset. Consequently, the belief was that traditional application and database planning efforts were sufficient to address ongoing data issues. As our corporate data stores have grown in both size and subject area diversity, it has become clear that a strategy to address data is necessary. Yet some still struggle with the idea that corporate data needs a comprehensive strategy. There’s no shortage of blue-sky thinking when it comes to organizations’ strategic plans and road maps. To many, such efforts are just a novelty. Indeed, organizations’ strategic plans often generate very few tangible results for organizations – only lots of meetings and documentation. A successful plan, on the other hand, will identify realistic goals along with a r
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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: SAS     Published Date: Aug 28, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: SAS     Published Date: Aug 28, 2018
Some organizations focus on the scary aspects of failing to comply with the EU General Data Protection Regulation. But there are many long-term benefits of following through with plans for sustainable GDPR compliance – such as gaining a competitive edge, or developing new products or services. To learn how organizations have approached compliance efforts, SAS conducted a global survey among 183 cross-industry businesspeople involved with GDPR. Based on the results, this e-book delves into the biggest opportunities and challenges faced. Read the e-book to: • Get advice from industry experts. • Find out what steps peers have taken. • Learn how an integrated approach from SAS can continue to guide your journey.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
With the amount of information in the digital universe doubling every two years, big data governance issues will continue to inflate. This backdrop calls for organizations to ramp up efforts to establish a broad data governance program that formulates, monitors and enforces policies related to big data. Find out how a comprehensive platform from SAS supports multiple facets of big data governance, management and analytics in this white paper by Sunil Soares of Information Asset.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
Starting data governance initiatives can seem a bit daunting. You’re establishing strategies and policies for data assets. And, you’re committing the organization to treat data as a corporate asset, on par with its buildings, its supply chain, its employees or its intellectual property. However, as Jill Dyché and Evan Levy have noted, data governance is a combination of strategy and execution. It’s an approach that requires one to be both holistic and pragmatic: • Holistic. All aspects of data usage and maintenance are taken into account in establishing the vision. • Pragmatic. Political challenges and cross-departmental struggles are part of the equation. So, the tactical deployment must be delivered in phases to provide quick “wins” and avert organizational fatigue from a larger, more monolithic exercise. To accomplish this, data governance must touch all internal and external IT systems and establish decision-making mechanisms that transcend organizational silos. And, it must provi
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SAS
Published By: SAS     Published Date: Aug 28, 2018
With the widespread adoption of predictive analytics, organizations have a number of solutions at their fingertips. From machine learning capabilities to open platform architectures, the resources available to innovate with growing amounts of data are vast. In this TDWI Navigator Report for Predictive Analytics, researcher Fern Halper outlines market opportunities, challenges, forces, status and landscape to help organizations adopt technology for managing and using their data. As highlighted in this report, TDWI shares some key differentiators for SAS, including the breadth and depth of functionality when it comes to advanced analytics that supports multiple personas including executives, IT, data scientists and developers.
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SAS
Published By: SAS     Published Date: Oct 03, 2018
Because terrorists and other criminals are already using technology to carry out their missions, intelligence professionals need to access all available, appropriate information, to extract important elements and process, analyze and disseminate it quickly to keep ahead of potential threats. The scale, complexity and changing nature of intelligence data can make it impossible to stay in front without the aid of technology to collect, process and analyze big data. This paper describes a solution for how this information can be quickly and safely shared with access based on a user's organizational responsibilities and need to know.
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SAS
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