big data analytics

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Published By: IBM     Published Date: Jul 19, 2016
Watch to learn how an enterprise-grade, multi-tenant solution can help you deploy Spark in a production environment to take advantage of · Faster time-to-results for big data analytics · Simplified deployment and management · Increased utilization of hardware resources"
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ibm, analytics, production environment, apache spark, idc research
    
IBM
Published By: IBM     Published Date: Nov 07, 2016
Apache Spark hit the scene in 2014 and has grown to be the most popular software project in the history of Open Source. Attend this webinar and learn more about; -What is Apache Spark? -Why, is it so popular? -Why is it important to you and your organization? Apache Spark is allowing companies to drive innovative ways to compete using one of the most valuable assets in the 21st century, Data! Apache Spark is the fastest growing framework for powering Big Data Analytics today and for the future. Register to attend this webcast and learn more.
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ibm, big data, platform computing, apache spark
    
IBM
Published By: IBM     Published Date: Nov 07, 2016
Is your software defined infrastructure (SDI) for high performance computing (HPC) and big data analytics meeting the needs of your growing business? Would you like to know how to justify the switching cost from unsupported open source software to a commercial grade SDI that ensures your resources are more effectively used cutting down time to market? This webcast will give you an overview of the true costs of building out and managing a HPC or Big Data environment and how commercial grade SDI software from IBM can provide a significant return on investment.
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ibm, platform computing, software defined infrastructure
    
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
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
This paper from Osterman Research, explores the origins of the "information problem" many organizations are now facing and presents a detailed discussion of how to calculate your current information costs as well as how to calculate the ROI of an information governance program.
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ibm, osterman, roi, big data, data, analytics, information governance
    
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: 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: Oct 02, 2018
Organizations are faced with providing secure authentication, authorization, and Single Sign On (SSO) access to thousands of users accessing hundreds of disparate applications. Ensuring that each user has only the necessary and authorized permissions, managing the user’s identity throughout its life cycle, and maintaining regulatory compliance and auditing further adds to the complexity. These daunting challenges are solved by Identity and Access Management (IAM) software. Traditional IAM supports on-premises applications, but its ability to support Software-as-a-Service (SaaS)-based applications, mobile computing, and new technologies such as Big Data, analytics, and the Internet of Things (IoT) is limited. Supporting on-premises IAM is expensive, complex, and time-consuming, and frequently incurs security gaps. Identity as a Service (IDaaS) is an SaaS-based IAM solution deployed from the cloud. By providing seamless SSO integration to legacy on-premises applications and modern cloud-
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Group M_IBM Q418
Published By: Cisco     Published Date: Jul 11, 2016
Companies rely on an expanding set of applications to compete in today's rapidly evolving business environment: - They rely on a fast-growing array of applications and devices (email, collaboration tools, and smartphones/tablets) to communicate and conduct business with customers and business partners. - They are creating, collecting, and repurposing large, unstructured data sets in life sciences, geophysics, media, and manufacturing. - They are collecting, storing, and analyzing more social and sensor-generated data about environments, products, customers, and transactions. The promise of better and faster data-driven decision making based on all this information is pushing big data and analytics (BDA) technology to the top of executive agendas. To succeed, CIOs must place a laserlike investment focus on datacenter solutions that allow them to deliver scalable, reliable, and flexible infrastructure for fast-growing BDA environments. Read more to learn how!
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Cisco
Published By: Cisco     Published Date: Jul 11, 2016
CTOs, CIOs, and application architects need access to datacenter facilities capable of handling the broad range of content serving, Big Data/analytics, and archiving functions associated with the systems of engagement and insight that they depend upon to better service customers and enhance business outcomes. They need to enhance their existing datacenters, they need to accelerate the building of new datacenters in new geographies, and they need to take greater advantage of advanced, sophisticated datacenters designed, built, and operated by service providers. IDC terms this business and datacenter transformation the shift to the 3rd Platform.
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Cisco
Published By: IBM     Published Date: May 01, 2017
If you function like most IT organizations, you've spent the past few years relying on mobile device management (MDM), enterprise mobility management (EMM) and client management tools to get the most out of your enterprise endpoints while limiting the onset of threats you may encounter. In peeling back the onion, you'll find little difference between these conventional tools and strategies in comparison to those that Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs) have employed since the dawn of the modern computing era. Their use has simply become more: Time consuming, with IT trudging through mountains of endpoint data; Inefficient, with limited resources and limitless issues to sort through for opportunities and threats; and Costly, with point solution investments required to address gaps in OS support across available tools. Download this whitepaper to learn how to take advantage of the insights afforded by big data and analytics thereby usher i
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ibm, endpoint management, mobile device management, enterprise mobility, os support, it organizations
    
IBM
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: IBM     Published Date: Sep 27, 2013
Analytics: The Real-World Use of Big Data - How innovative enterprises in the midmarket extract value from uncertain data 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, big data, big data solutions, midmarket businesses, analytics
    
IBM
Published By: IBM     Published Date: Oct 31, 2013
Improve customer satisfaction, identify trends and make smarter marketing decisions with IBM Social Media Analytics.
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social media, big data, data-driven marketing, marketing analytics, performance analytics, business analytics, metrics, data, driver-based campaign, campaign optimization, marketing campaign, analytics software, customer experience, c-suite, customer relationship management, crm, facebook, twitter
    
IBM
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, variety, customer analytics, trends and insights, information management, data security, integration, variety of data, analytic accelerator, infrastructure
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
According to Dr. Barry Devlin of 9sight Consulting, the truth behind all the talk about big data and the possibilities it can offer is not hard to see, provided that organizations are willing to return to the principles of good data management processes.
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ibm, big data, 9sight consulting, data, it management, maximize business, deployment, business opportunities, big data usage, data warehouse, data center, business analytics, big data offerings, core business data, analytic data, puredata system, data virtualization, data integration, data types, data quality
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
In this Advisory, Clabby Analytics looks more closely at the importance of implementing an integrated infrastructure — and its relationship to business analytics. The paper will examine the business analytics workloads, discuss how these workloads put different demands on the underlying systems and infrastructure, and provide guidance designing an integrated business analytics environment that will provide organizations with high performance, resiliency, and a scalable growth path.
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analytics, power 7, big data, power systems, virtualization, ibm, ibm power systems, infrastructure, storage, integrated infrastructure, clabby analytics, three maxims, buying criteria, analytics buying, system storage
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
Watson’s success in the Jeopardy! challenge was inspiring, but the business impact of optimized systems design is just beginning. With smarter analytics solutions optimized on IBM Power Systems, you can put Watson's technology to work and ensure that you
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power 7, big data, watson, decision making, power systems, virtualization, spss collaboration, ibm, ibm power systems, analytics
    
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, data generation, data management, storage, acceleration, business intelligence, data warehouse
    
IBM
Published By: IBM     Published Date: Mar 05, 2014
IBM Big Data Stampede fuses the strength of IBM’s services, products and skills to minimize the barriers of Big Data initiatives and provide organizations with quick success. Your Big Data Stampede includes an assessment to identify the high value starting points with Big Data. We work with you to unearth trouble areas and complex problems for resolution through leveraging Big Data. Read this data sheet to learn more.
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ibm, ibm big data big data, information management, data management, big data technology, business analytics, insights, acceleration, productivity
    
IBM
Published By: IBM     Published Date: Apr 18, 2014
For many enterprises System z is central to modern analytics because of the vast quantities or rich data stored upon it – not to mention excellent qualities of service. Carl Olofson, an IDC analyst looks, at the role of the mainframe in relation to big data, how it has become a hub for modern day analytics, its ability to integrate information from other sources to enhance business decisions and how it is positioned for the future. Download this paper and learn.
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ibm, mainframe, platform, big data, analytics, big data and analytics, bda, big data technology, system z
    
IBM
Published By: IBM     Published Date: Jul 07, 2014
In this report, Business Value of Big Data on Power Systems, NC State University talks about unlocking the business value of big data, and how IBM Power Systems can deliver the foundation for organizations to bring insight to the point of impact faster.
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ibm, big data, analytics, power systems, business value, business insights, ibm power systems
    
IBM
Published By: Cisco     Published Date: Dec 21, 2016
CTOs, CIOs, and application architects need access to datacenter facilities capable of handling the broad range of content serving, Big Data/analytics, and archiving functions associated with the systems of engagement and insight that they depend upon to better service customers and enhance business outcomes. They need to enhance their existing datacenters, they need to accelerate the building of new datacenters in new geographies, and they need to take greater advantage of advanced, sophisticated datacenters designed, built, and operated by service providers. IDC terms this business and datacenter transformation the shift to the 3rd Platform.
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Cisco
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
Published By: Storiant     Published Date: Mar 16, 2015
This Technology Spotlight examines the issues that are driving organizations to replace older archive and backup-and-restore systems with business continuity and always-available solutions that can scale to handle extreme data growth while leveraging a cloudbased pricing model.
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storiant, data growth, data center, online data, data storage, storiant, big data, analytics implementations, cloudbased pricing model, long-term storage services solution, long-term storage market
    
Storiant
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