big data problems

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By: NetApp     Published Date: Dec 13, 2013
Despite the hype, Big Data has introduced critical challenges for modern organizations – and unprepared organizations risk getting buried beneath an avalanche of information. In this informative webcast, join industry and business intelligence (BI) expert Wayne Eckerson, as he tackles the challenges of Big Data. Uncover practical tips and tactics for driving value with your Big Data platform – watch now to learn more.
Tags : big data problems, how to get the most from your big data
     NetApp
By: RedPoint     Published Date: Sep 22, 2014
The emergence of YARN for the Hadoop 2.0 platform has opened the door to new tools and applications that promise to allow more companies to reap the benefits of big data in ways never before possible with outcomes possibly never imagined. By separating the problem of cluster resource management from the data processing function, YARN offers a world beyond MapReduce: less encumbered by complex programming protocols, faster, and at a lower cost. Some of the topics discussed in this paper include: • Why is YARN important for realizing the power of Hadoop for data integration, quality and management? • Benchmark results of MapReduce vs. Pig vs. visual “data flow” design tools • The 3 key features of YARN that solve the complex problems that prohibit businesses from gaining maximum benefit from Hadoop. Download this paper to learn why the power of Hadoop 2.0 lies in enabling applications to run inside Hadoop, without the constraints of MapReduce.
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     RedPoint
By: Dell EMC     Published Date: May 10, 2017
While just about everyone is writing about how IT and the businesses it serves need to be transformed, the actual industry answers to both digital and IT transformation remain unclear at best. Are transformational initiatives all about analytics and big data? Or are they about the move to cloud in all its varieties? Support for mobile? More agile ways of working and developing software? Or are they actually all about crafting teams to promote more proactive dialog between the business and IT? The truth is, of course, digital and IT transformation depend on all of the above and more. They also depend on a resilient infrastructure that’s easily adapted to changing business priorities without requiring long hours spent on maintenance, updates, and addressing problems of service availability. But making all this work clearly and cohesively is far beyond the purview of almost any solution today—whether from a software management perspective or from a hardware infrastructure perspective.
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     Dell EMC
By: MarkLogic     Published Date: Jun 09, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic
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     MarkLogic
By: HP - Enterprise     Published Date: Jun 04, 2013
Businesses are overwhelmed with data; it’s a blessing and a curse. A curse because it can overwhelm traditional approaches to storing and processing it. A blessing because the data promises business insight that never existed earlier. The industry has spawned a new term, “big data,” to describe it. Now, IT itself is overwhelmed with its own big data. In the press to roll out new services and technologies—mobility, cloud, virtualization—applications, networks, and physical and virtual servers grow in a sprawl. With them comes an unprecedented volume of data such as logs, events, and flows. It takes too much time and resources to sift through it, so most of it lies unexplored and unexploited. Yet like business data, it contains insight that can help us solve problems, make decisions, and plan for the future.
Tags : data research, big data, virtualization, applications, networks
     HP - Enterprise
By: IBM     Published Date: Jul 26, 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. High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-centric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
Tags : customer analytics, data matching, big data, competitive advantage, customer loyalty
     IBM
By: IBM     Published Date: Jul 06, 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.
Tags : ibm, mdm, big data, data management, data matching, customer analytics, data science
     IBM
By: MarkLogic     Published Date: Nov 08, 2016
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Download now to learn more.
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     MarkLogic
By: MarkLogic     Published Date: Nov 07, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic.
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     MarkLogic
By: FICO     Published Date: Jan 11, 2018
Many organizations consider optimization only for their largest or most challenging business problems, often utilizing a small number of Operations Research professionals. But in our age of Big Data, market globalization and increased competition, many organizations are successfully making the case that optimization can be applied to a wider variety of business and operational decisions, and be developed by a new group of users — the organization’s business analysts. With a proven track record of results demonstrating that organizations can increase profitability with business analysts applying optimization to many types of business problems, FICO’s proven development methodology is giving organizations the confidence to extend optimization practices across their enterprises.
Tags : business analyst, optimization, fico, partnership, credit, collections, banking, finance
     FICO
By: SteamSets     Published Date: Sep 24, 2018
The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. One area that benefits from replatforming is the data warehouse. According to research firm Gartner, “starting in 2018, data warehouse managers will benefit from hybrid architectures that eliminate data silos by blending current best practices with ‘big data’ and other emerging technology types.” There’s undoubtedly a lot to ain by modernizing data warehouse architectures to leverage new technologies, however the replatforming process itself can be harder than it would at first appear. Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.
Tags : replatforming, age, data, lake, apache, hadoop
     SteamSets
By: QlikTech     Published Date: Aug 27, 2013
There is an incredible amount of interest in the topic of Big Data at present: for some organisations its use is an operational reality, providing unprecedented ability to store and analyse large volumes of disparate data that are critical to the organization’s competitive success. It has enabled people to identify new opportunities and solve problems they haven’t been able to solve before. Download this whitepaper to learn more.
Tags : big data, qlikview, big data solutions, opportunity, business opportunity, competitive success, store, analyse, operational reality
     QlikTech
By: New Relic     Published Date: Mar 17, 2015
Application performance management (APM) focuses on monitoring, maintaining, and optimizing the performance and health of business applications across development, test, datacenter, and network environments. As mission-critical enterprise application environments become more complex because of the increased use of cloud, big data, and mobility, APM is becoming a top priority for IT teams that need to quickly and cost effectively track end-to-end application performance, identify and remediate the root cause of performance problems, and maintain service levels required by end users and business stakeholders. SaaS-delivered APM solutions offer rapid time to value for IT organizations that need to implement APM quickly with minimal disruption to the business.
Tags : apm, application performance management, big data, application performance, mobility, data center, data management
     New Relic
By: TIBCO     Published Date: Aug 05, 2014
This ebook explains how the TIBCO Fast Data architecture delivers the right information—and the right decision—at the right place and time.
Tags : tibco, tibco software, big data, business intelligence, esb, enterprise service bus, soa, application integration, service management, decision making
     TIBCO
By: HP     Published Date: Mar 31, 2015
No business is immune to the threat of IT downtime caused by natural and manmade disasters. Natural disasters—such as earthquakes, tsunamis, hurricanes, fires, and floods—can happen with little to no advanced warning. But the bigger risk is often human-induced events—from simple IT configuration errors to significant data center problems. If you lack a rock-solid disaster recovery (DR) plan, any of these unpredictable events—natural or manmade—could bring your business and its revenue streams to a halt. Yet many organizations are not well prepared for the unknown. The randomness of such events lulls people into a sense of false security—“That’s not likely to happen here.” While you can hope to avoid events that threaten the continuity of your business, the reality remains unchanged: Disasters happen—so you need to prepare for them. Are you prepared? Please download this eBook to find out!
Tags : disaster recovery, natural disasters, data center, hackers, hardware failure, software failure, planning, disaster readiness, security
     HP
By: IBM     Published Date: May 02, 2014
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.
Tags : ibm, big data, big data success, big data platform, big data stampede, high value, assessments, big data solutions, transfer knowledge, skills enablement, enablement and success, minimize barriers
     IBM
By: IBM     Published Date: Nov 06, 2014
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.
Tags : big data, data integration, analytics, customer matching, ibm
     IBM
By: IBM     Published Date: Jan 09, 2015
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.
Tags : ibm, big data, insights, infosphere, data management, dashboards, value, data matching, analytics, challenges, hadoop
     IBM
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.
Tags : ibm, mdm, big data, data management, data matching, customer analytics
     IBM
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.
Tags : customer analytics, data analysis, competitive advantage, understanding your customer base
     IBM
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.
Tags : ibm, ibm big data big data, information management, data management, big data technology, business analytics, insights, acceleration, productivity
     IBM
By: IBM     Published Date: Jan 14, 2015
Big data has been big news in recent years. Organizations recognize that they must now begin to focus on using big data technologies to solve business problems. The pressure is on for organizations to move past the discussion phase toward well-planned projects.
Tags : big data, data management, data exploration, gain visibility, security extension, business intelligence, explore data, data analytics
     IBM
By: Viavi Solutions     Published Date: Apr 01, 2015
Big data projects are becoming reality for nearly every major enterprise. According to a recent survey, 49 percent of respondents say they are implementing, or likely to implement big data projects in the future. Twelve percent already have. With big data comes surprising impacts to your network. The 4 Steps to Surviving Big Data white paper will help you identify problems before they start.
Tags : big data, data projects, network performance, data management, network impact
     Viavi Solutions
By: Pure Storage     Published Date: Apr 18, 2018
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data. Amazon CEO Jeff Bezos spoke about the potential of artificial intelligence and machine learning at the 2017 Internet Association‘s annual gala in Washington, D.C., “It is a renaissance, it is a golden age,” Bezos said. “We are solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades. Natural language understanding, machine vision problems, it really is an amazing renaissance.” Machine learning and AI is a horizontal enabling layer. It will empower and improve every business, every government organization, every philanthropy
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     Pure Storage
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