ibm analytics

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Published By: IBM     Published Date: May 17, 2016
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.
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ibm, intelligent business solutions, big data, transaction data, business analytics
    
IBM
Published By: IBM     Published Date: May 17, 2016
Is your data architecture up to the challenge of the big data era? Can it manage workload demands, handle hybrid cloud environments and keep up with performance requirements? Here are six reasons why changing your database can help you take advantage of data and analytics innovations. 
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ibm, business analytics, business intelligence, data, analytics, database
    
IBM
Published By: IBM     Published Date: May 17, 2016
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
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ibm, big data, inline analytics, business analytics, roi
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
This white paper is written for SAP customers evaluating their infrastructure choices, discussing database technology evolution and options available.
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ibm, always on business, analytics, database, database platform, sap, blu, db2
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
This ebook presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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ibm, database, database change, analytics
    
IBM
Published 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.
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customer analytics, data matching, big data, competitive advantage, customer loyalty
    
IBM
Published By: IBM     Published Date: Jun 16, 2015
Read the white paper to learn how a good data center strategy can help you prepare for the rigors and unpredictability of emerging technologies. Find out how IBM’s predictive analytics are helping companies build more accurate, forward-looking data center strategies and how those strategies are leading to more agile, efficient and resilient infrastructures.
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data center, predictive analytics, data center strategy, resilient infrastructure, cloud computing, social collaboration, business analytics, emerging technologies
    
IBM
Published By: IBM     Published Date: Jan 27, 2016
This paper describes how predictive analytics can play a critical role in your threat and risk strategy.
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ibm, threat, risk, management, security, analytics, fraud
    
IBM
Published By: IBM     Published Date: Jan 27, 2016
This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics.
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ibm, analytics, predictive, strategy, competitive advantage
    
IBM
Published By: IBM     Published Date: Jan 27, 2016
Forrester Research evaluated 13 big data predictive analytics solution vendors and IBM emerged as one of the three leaders. Learn why.
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ibm, forrester wave, big data, predictive analytics
    
IBM
Published By: IBM     Published Date: May 16, 2016
Our objective in this Checklist Report is to share best practices that will position the reader to take advantage of a cloud-based data warehousing solution.
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ibm, tdwi, checklist report, data warehousing, cloud, analytics, analytic architecture, warehousing
    
IBM
Published By: IBM     Published Date: May 16, 2016
The data-driven organization is the new benchmark for success. Firms that harness data to dictate strategic and tactical decisions companywide make more informed business plans, better optimize operations, improve customer interactions, and provide competitive edge. To achieve these benefits, organizations increasingly see data refinement - transforming raw data from various sources into relevant and actionable information and delivering it through self - service access to any user who needs it - as the path toward success by helping break though immature processes and legacy systems. However, data refinement only functions as well as the strategies and approaches behind it. Organizations that do not understand the right way to embrace refinement will fail to catch up to competitors that have mastered the correct approach.
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ibm, forrester, data-driven organization, data, analytics, analytic architecture
    
IBM
Published By: IBM     Published Date: May 19, 2016
In our 21-criteria evaluation of the dynamic case management (DCM) market, we identified the 14 most significant software vendors — Appian, bpm’online, Column Technologies, DST Systems, Eccentex, IBM, Isis Papyrus, Lexmark Enterprise Software, MicroPact, Newgen Software, OnBase by Hyland, OpenText, Pegasystems, and TIBCO Software — and researched, analyzed, and scored them. The evaluation focused on providers’ adaptive, analytics, and mobile features, all critical to helping enterprises tackle increasing volumes of varied and unstructured work. This report helps enterprise architecture (EA) professionals select the best providers to meet their unique needs.
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ibm, forrester, forrester wave, dynamic case management, dcm, software vendors, software
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
This video demonstrates how IBM’s Behavior Based Customer Insight for Banking leverages predictive analytics to help you personalize customer engagement and deliver customized actions. The solution leverages advanced predictive models to analyze customer transactions and spending behavior to more deeply understand customer needs and propensities, anticipate life events, and help provide a unique customer experience.
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ibm, banking, finance, consumer insights, business intelligence, business anlytics
    
IBM
Published By: IBM     Published Date: May 26, 2017
A significant challenge for many organizations has been enabling their analysts to find the "unknown unknown." Whether that unknown is malware lurking within the enterprise or within slight variations in fraudulent transactions, the result has been the same: enterprises continue to fall victim to cybercrime. IBM is addressing this challenge with IBM i2 Enterprise Insight Analysis. By pairing multi-dimensional visual analysis capabilities with powerful analytics tools, IBM is giving the analyst team an effective early-detection, cyberintelligence weapon for its arsenal.
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security. ibm, ibm i2, cyber-intelligence, fraud, malware
    
IBM
Published By: IBM APAC     Published Date: May 14, 2019
Clients can realize the full potential of artificial intelligence (AI) and analytics with IBM’s deep industry expertise, technology solutions and capabilities and start to infuse intelligence into virtually every business decision and process. IBM’s AI & Analytics Services organization is helping enterprises get their data ready for AI and ultimately achieve stronger data-driven decisions; access deeper insights to provide improved customer care; and develop trust and confidence with AI-powered technologies focused on security, risk and compliance. Artificial intelligence (AI) is moving beyond the hype cycle, as more and more organizations seek to adopt AI-related technologies. These organizations are focusing on prioritizing functional areas and use cases, placing a stronger emphasis on topline growth, taking up a renewed interest in their data infrastructure and articulating greater unease about the skills of their knowledge workers. This report explores how they are approaching str
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IBM APAC
Published By: IBM     Published Date: Nov 10, 2015
In the face of an overabundance of numbers, knowing which metrics are most important can be a real challenge for Human Resource (HR) leaders and hiring managers. Fortunately, new analyses from the IBM Smarter Workforce Institute can provide some guidance.
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hiring, ibm, smarter workforce institute, analytics
    
IBM
Published By: IBM     Published Date: Jan 27, 2016
Read this white paper to discover how predictive analytics and cognitive commerce make it possible to get instant access to integrated information and actionable insights so you can deliver superior—and profitable—interactions with customers.
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ibm, data, insights, results, analytics, cognitive commerce
    
IBM
Published By: IBM     Published Date: Feb 02, 2016
Read this editorial to learn about the challenges and opportunities ahead for energy companies, and find out how utilities can use analytics to improve satisfaction by gaining insight into consumption and billing patterns—as well as the products and services that interest customers most.
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ibm, analytics, energy, utilities, customer experience, social media, data, customer management
    
IBM
Published By: IBM     Published Date: Feb 02, 2016
Energy firms should build and nurture a customer-centric culture delighting clients while maximizing operational and financial results. In doing so, we’ll highlight the crucial role analytics plays in helping energy firms ensure operational efficiency and customer satisfaction.
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ibm, energy, analytics, utility, customer experience, data, customer satisfaction, social media
    
IBM
Published By: IBM     Published Date: Apr 01, 2016
Traditional business intelligence (BI) looks backward at what has happened. In today’s marketplace, enterprises need to look ahead. In this eGuide from TDWI, you'll discover how advances in predictive analytics are enabling organizations to use insights about the past and present to make accurate predictions about the future.
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ibm, business intelligence, ibm connect, predictive analytics
    
IBM
Published By: IBM     Published Date: Apr 11, 2016
This paper explores why your business needs the latest operational decision management (ODM) solutions to help turn data insights into action. Discover how IBM Operational Decision Manager software and the IBM Business Process Manager platform work together to: *Recognize patterns that suggest opportunity or risk *Create and shape business events by automating decisions *Bring more dimension and precision to decision making by applying analytics to big data *Help you implement the right business processes by understanding data in context.
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ibm, smarter process, operational decision management, odm
    
IBM
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
    
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
    
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
    
IBM
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