data insights

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Published By: IBM     Published Date: Oct 13, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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ibm, mdm, big data, ibm infosphere, mdm advantagw, knowledge management, enterprise applications
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
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ibm, analytics, big data, hadoop, enterprise, ibm biginsights, apache, enterprise management
    
IBM
Published By: IBM     Published Date: Oct 17, 2016
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
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ibm, analytics, spss, stats, modeler, predictive analytics, enterprise applications, data management
    
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, knowledge management, enterprise applications
    
IBM
Published By: IBM     Published Date: Oct 28, 2016
In this webinar, you will learn: - How to create a safe environment for honest feedback so it’s an invitation, not an imposition - Best practices for collecting feedback, from unstructured conversations to regular pulse surveys - What to do with the data you’ve collected, and how to use insights to create action plans that result in happier employees and better business performance
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ibm, engagement social, employee engagement, kenexa, knowledge management, enterprise applications
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
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ibm, aps data, data science, open data science, analytics, enterprise applications
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
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ibm, analytics, aps data, open data science, data science, data engineers, enterprise applications
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
Data matters more than ever to business success. But value does not come from data alone. Rather, it comes from the insights enabled by data. No matter what your role is, or where you are in your data journey, you are looking for ways to drive innovation.
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ibm, analytics, aps data, open data science, data science, apache spark, enterprise applications
    
IBM
Published By: IBM     Published Date: Jan 27, 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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IBM
Published By: IBM     Published Date: Jan 27, 2017
Cloud- based data presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on- premises data with new third- party cloud- based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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IBM
Published By: IBM     Published Date: Jan 27, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, as discussed in “The truth about information governance and the cloud,” most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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IBM
Published By: IBM     Published Date: Jan 27, 2017
In this era of digital transformation, business and IT leaders across all industries are looking for ways to easily and cost-effectively unlock the value of enterprise data and use it to deliver new customer experiences while fueling business growth. The digital economy is changing the way organizations gather information, gain insights, reinvent their businesses and innovate both quickly and iteratively.
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IBM
Published By: IBM     Published Date: Feb 01, 2017
Ordinary analytics tools can’t keep up with today’s digital, multichannel and demanding customers. This guide highlights three major challenges associated with traditional analytics and how innovative strategies combined with IBM’s Customer Experience Analytics solution can solve them.
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ibm, commerce, customer analytics, customer insights, enterprise applications
    
IBM
Published By: IBM     Published Date: Feb 02, 2017
With 2.5 quintillion bytes of data created every day, it’s getting harder to separate the signals from the noise and discern the insights from the hindsight. Discover 10 key trends that will shape marketing in 2017 and get ideas for deepening customer connections, growing brand value and fueling strategic growth.
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ibm, commerce, marketing, marketing benchmark, marketing trends
    
IBM
Published By: IBM     Published Date: Mar 29, 2017
Not just some data—all of it. Internal, external, structured, unstructured, historical, real-time. And what if you could do it without a huge infrastructure project? You can. Take a closer look at how three companies capitalized on more data—almost instantly—with IBM® BigInsights® on Cloud.
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analyze, data, cloud, ibm, analytics
    
IBM
Published By: IBM     Published Date: Mar 30, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on-premises data with new third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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cloud security, electronic security, health care, security risk management, user authentication, cloud technology
    
IBM
Published By: IBM     Published Date: Apr 03, 2017
Businesses today certainly do not suffer from a lack of data. Every day, they capture and consume massive amounts of information that they use to make strategic and tactical decisions. Yet organizations often lack two critical capabilities when it comes to making the right decisions for the business: the ability to make accurate predictions about the future, and to then use those predicted insights in conjunction with organizational goals to identify the best possible actions they should take. The combination of predictive analytics and decision optimization provides organizations with the ability to turn insight into action. Predictive analytics offers insights into likely scenarios by analyzing trends, patterns and relationships in data. Decision optimization prescribes best-action recommendations given an organization’s business goals and business dynamics, taking into account any tradeoffs or consequences associated with those actions.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources, data optimization
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on-premises data with new third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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data integration, lifecycle management, hybrid environment, cloud-based data, information governance, decision making
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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cloud-based data, data quality, data management, hybrid environment, decision making
    
IBM
Published By: IBM     Published Date: Apr 19, 2017
Data is only as good as the insights it produces, the actions it influences, and the results it fosters. That’s the secret recipe for data management. Your business stakeholders depend on data-based insights to drive decisions and priorities throughout the organization. Insights based on sound data practices can give your business a competitive advantage in the marketplace. Is your data management system ready to support your business? Find out using Forrester’s Data Management Infrastructure Self-Assessment Tool. IBM has licensed this tool to help you identify the areas of strength and opportunities for improvement.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
IBM
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: IBM     Published Date: May 12, 2017
In today’s world, the data is flowing from all directions: social media, phones, weather, location and sensor equipped devices, and more. Competing in this digital age requires the ability to analyze all of this data, and use it to drive decisions that mitigate risk, increase customer satisfaction and grow revenue. Using a combination of proprietary software and open source technology can give your data scientists and statisticians the analytical power they need to find and act on insights quickly. IBM® SPSS® Statistics provides all of the data analysis tools you need, and integrates with thousands of R extensions for maximum power and flexibility. In this next Data Science Central Webinar event, we will show how SPSS Statistics can help you keep up with the influx of new data and make faster, better business decisions without coding.
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ibm, spss, data analysis, statistics, risk mitigation
    
IBM
Published By: IBM     Published Date: May 26, 2017
Securing your infrastructure, your customer interactions and protecting your data are critical to preserving your reputation and your bottom line. Many cyber attacks remain undetected for up to eight months1 and can cost an organization an average of 11 million USD.2 Today’s cyber actors are becoming more sophisticated, agile and capable of getting past any network security. Organizations must evolve, replacing traditional defensive security strategies with a proactive, intelligence-driven offense to prevent and disrupt these threats. IBM® i2® Enterprise Insight Analysis is a next generation intelligence solution that enables organizations to incorporate cyber threat hunting into their security strategy and turn their defense into a proactive offense.It helps organizations uncover critical insights about their threats and threat actors so they can mitigate and counter more threats with a combination of multi-dimensional visualte analysis capabilities
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ibm, ibm i2, cyber security, customer interaction, enterprise insight analysis
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
Business leaders are eager to harness the power of big data. However, as the opportunity increases, ensuring that source information is trustworthy and protected becomes exponentially more difficult. If not addressed directly, end users may lose confidence in the insights generated from their data—which can result in a failure to act on opportunities or against threats. Information integration and governance must be implemented within big data applications, providing appropriate governance and rapid integration from the start. By automating information integration and governance and employing it at the point of data creation, organizations can boost confidence in big data. A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamle
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mdm, big data, automation, organization
    
IBM
Published By: IBM     Published Date: Jul 26, 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. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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scalability, data warehousing, resource planning
    
IBM
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