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big data analytics

Results 101 - 125 of 382Sort Results By: Published Date | Title | Company Name
Published By: Splunk     Published Date: Nov 29, 2018
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences. Download the e-book to learn how: Micron Technology reduced number of IT incidents by more than 50% Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk
Published By: Splunk     Published Date: Dec 11, 2018
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences. Download this executive brief from CIO to learn: 5 steps to an effective predictive IT strategy Where AI can help, and where it can’t How to drive revenue and exceptional customer experiences with predictive analytics
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk
Published By: Amazon Web Services     Published Date: Oct 09, 2017
As easy as it is to get swept up by the hype surrounding big data, its just as easy for organisations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt. However, given big data's power to transform business, it's critical that organisations overcome these challenges and realise the value of big data. The cloud can help organisations to do so. Drawing from IDG's 2015 Big Data and Analytics Survey, this white paper analyses the top five challenges companies face when undergoing a big data initiative and explains how they can effectively overcome them.
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amazon, web services, intel, migration, data warehousing, organization optimization, security, software
    
Amazon Web Services
Published By: Dassault Systèmes     Published Date: Jul 21, 2017
Obtaining a first-mover competitive advantage or faster time-to-market requires a new wave in analytics. Dassault Systèmes remains a leading innovator in Product Lifecycle Management (PLM) and has invested heavily in analytical technologies to further drive business benefits for its customers in the related areas of planning, simulation, insight and optimization. This white paper examines the challenges peculiar to PLM and why Dassault Systèmes’ EXALEAD offers the most appropriate solution. It also clearly positions EXALEAD PLM Analytics alongside related technologies like BI, data-warehousing and Big Data solutions. Understand and implement PLM Analytics to access actionable information, support accurate decision-making, and drive performance.
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product solutions, lifecycle management, tech products, data management tools, pdm, plm, process automation, product development speed
    
Dassault Systèmes
Published By: Infor     Published Date: Mar 07, 2017
Big data is more than a buzz word. In recent years, analytics systems have quickly become an essential tool for businesses to gather and interpret various forms of information.
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Infor
Published By: Pure Storage     Published Date: Oct 09, 2018
Apache® Spark™ has become a vital technology for development teams looking to leverage an ultrafast in-memory data engine for big data analytics. Spark is a flexible open-source platform, letting developers write applications in Java, Scala, Python or R. With Spark, development teams can accelerate analytics applications by orders of magnitude
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Pure Storage
Published By: IBM     Published Date: Apr 19, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data management
    
IBM
Published By: IBM     Published Date: Apr 19, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, data management
    
IBM
Published By: IBM     Published Date: Apr 19, 2016
The use of analytics will define the successful midmarket business of the next decade, just as it will define the successful larger organization in this information age. The past decade has seen rapid change in the business climates with an explosion of global competition and economic uncertainty. Despite this, many midmarket companies have thrived by using their size and agility as a competitive advantage. Certainly they have fewer resources than large corporations who are able to invest large sums in IT. However, small yachts can turn and adjust their course much quicker than large cruise ships. The same came be said for midmarket companies. The most successful organizations are ones that can react the quickest to changes in the market place. Midmarket companies can take advantage of their smaller size by being more agile and quicker to change, or even reinvent themselves, to respond to the market.
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ibm, ibm pure data system, big data, data analytics, analytics architecture, competitive advantage, midmarket organization, data management
    
IBM
Published By: IBM     Published Date: Apr 22, 2016
The upside of disruption: Reinventing business processes, organizations and industries in the wake of the digital revolution
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ibm, ibm big data and analytics, ibm big data, trusted data, big data, data management
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
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ibm, ibm pure data system, big data, data analytics, analytics architecture, knowledge management, enterprise applications, data management
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, knowledge management, data management
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
In an environment where data is the most critical natural resource, speed-of-thought insights from information and analytics are a critical competitive imperative.
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ibm, data warehouse, big data, analytics, data warehouse, business intelligence, knowledge management, data management
    
IBM
Published 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.
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ibm, mdm, big data, data management, data matching, customer analytics, data center
    
IBM
Published By: IBM     Published Date: Jul 08, 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, data management
    
IBM
Published By: IBM     Published Date: Jul 08, 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, knowledge management
    
IBM
Published By: IBM     Published Date: Jul 08, 2016
Read this Forrester whitepaper to learn more about the critical, yet often overlooked, role that data classification and data discovery can play in reducing your organization’s risk and enhancing security.
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ibm, forrester, data discovery, big data, data, analytics, information governance, knowledge management
    
IBM
Published By: IBM     Published Date: Jul 14, 2016
How do you keep 130,000 guests safely entertained, fed, watered and informed in a sustainable way? Roskilde Festival knew that the critical insights lay hidden in huge volumes of real-time data. The Copenhagen Business School used IBM technologies to build a cloud big data lab that correlates information from multiple sources, delivering valuable insight for planning and running the festival. Download to learn more.
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ibm, datamart on demand, data, analytics, big data, real-time data, cloud, cloud data analytics
    
IBM
Published By: IBM     Published Date: Jul 14, 2016
IBM SPSS Solutions offer a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end.
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ibm, big data, data analytics, ibm spss, predictive business, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
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ibm, ibm pure data system, big data, data analytics, analytics architecture, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, enterprise applications, data management
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
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-c entric 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.
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IBM
Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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Group M_IBM Q2'19
Published By: F5 Networks Inc     Published Date: Mar 30, 2018
It seems like every day there’s another article about IoT, big data analytics, and cloud architectures—and their unlimited potential for companies trying to gain a competitive edge in this digital world. If your business is in the midst of a digital transformation (and chances are, it is), you’re probably already enjoying some the benefits of the public cloud: economies of scale, preconfigured solutions that can be spun up with a few clicks, utility billing, and more. What you may not have heard, however, is how the shared security model of the public cloud affects your security responsibilities —and how it can be used to your advantage in these multicloud environments.
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roi, cloud, security, architectures, business, economies
    
F5 Networks Inc
Published By: EMC Corporation     Published Date: May 27, 2014
ESG Whitepaper: New security risks and old security challenges often overwhelm legacy security controls and analytical tools. This ESG white paper discusses why today's approach to security management—that depends on up-to-the-minute situational awareness and real-time security intelligence—means organizations are entering the era of big data security analytics.
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emc, security operations, security analytics, intelligence-driven security, threat detection, security monitoring, critical incident response, security
    
EMC Corporation
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