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Published By: IBM     Published Date: Apr 29, 2014
For banks, mining data from social media can be a significant way to gain insights into customer mindsets and behavior, but effectively and accurately capturing and processing this unstructured data to gain useful customer insight requires sophisticated tools and advanced analytics.
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ibm, banking, data mining, social media, consumer insights, business analytics, social business, business technology, finance
    
IBM
Published By: IBM     Published Date: Aug 05, 2014
Watson Explorer provides organizations with a combined, trusted 360-degree view of both structured and unstructured data. The solution indexes information from unstructured data sources (PDFs, Microsoft SharePoint, flat files, social media, blogs and so on) as well as structured sources for search and discovery. Organizations can leverage their data in place, respecting existing security models when creating this virtual access point to all information. Watson Explorer requires trusted master data to ensure that links are accurate and reliable, so the end user can confidently leverage a holistic view of a customer or product.
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ibm, data, customer, watson explorer, master data, structured, it management, data management
    
IBM
Published By: IBM     Published Date: Aug 05, 2014
There is a lot of discussion in the press about Big Data. Big Data is traditionally defined in terms of the three V’s of Volume, Velocity, and Variety. In other words, Big Data is often characterized as high-volume, streaming, and including semi-structured and unstructured formats. Healthcare organizations have produced enormous volumes of unstructured data, such as the notes by physicians and nurses in electronic medical records (EMRs). In addition, healthcare organizations produce streaming data, such as from patient monitoring devices. Now, thanks to emerging technologies such as Hadoop and streams, healthcare organizations are in a position to harness this Big Data to reduce costs and improve patient outcomes. However, this Big Data has profound implications from an Information Governance perspective. In this white paper, we discuss Big Data Governance from the standpoint of three case studies.
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ibm, data, big data, information, healthcare, governance, technology, it management, data management
    
IBM
Published By: IBM     Published Date: Oct 22, 2014
Great service is delivered one customer at a time and improving interactions across all channels means truly understanding customer wants and needs. Massive amounts of unstructured data exist in your organization and can deliver customer insight that is specific, relevant and actionable. Learn how to harness that data to provide great customer service.
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customer service, service quality, customer satisfaction, content management, it management, data management, business intelligence, business management
    
IBM
Published By: IBM     Published Date: Feb 24, 2015
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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big data, ibm, big data outcomes, information governance, big data analytics, it management, data management, data center
    
IBM
Published By: IBM     Published Date: Mar 18, 2015
Read this ebook from Aberdeen to learn why leading organizations are moving away from the chaos of multiple methods to a single managed file transfer platform, and get best practices for developing a secure, best-in-class file transfer process of your own.
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file transfer platform, file transfer process, ibm, unstructured data, file delivery, personal finance, finance
    
IBM
Published By: IBM     Published Date: Apr 06, 2015
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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big data, analytics, unstructured content, enterprise information, ibm, security, it management, knowledge management, storage, data management
    
IBM
Published By: IBM     Published Date: Apr 29, 2015
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.
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data warehouse, big data, unstructured data, implementations, business intelligence, database development, quality assurance, productivity, data warehousing
    
IBM
Published By: IBM     Published Date: Jul 01, 2015
The impact of streaming analytics and leveraging expertise in the healthcare sector.
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data insights, healthcare data, healthcare analytics, unstructured content analytics, computation-intensive analytics, ibm big data, enterprise-class data management
    
IBM
Published By: IBM     Published Date: Jul 08, 2015
For years, organizations have recognized that a better understanding of customers can translate to more sales, increased customer satisfaction and reduced customer churn. Initiatives focused on a 360-degree view of the customer have gone a long way toward providing those benefits by synthesizing customer profiles, sales history and other structured data from multiple sources across the enterprise. But today, customer-centric organizations are discovering that there is more opportunity for growth when they enhance that 360-degree view with information from more sources, both within and beyond the enterprise (see Figure 1). Information in email messages, unstructured documents and social media sentiments—previously beyond reach—is now extending the 360-degree view.
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ibm, e360, customer satisfaction, customer retention, sales history, big data, it management, knowledge management, enterprise applications
    
IBM
Published By: IBM     Published Date: Oct 12, 2015
This IBM-commissioned profile of government information management professionals examines the challenges of dealing with the increase in digital and unstructured content as well as the roles that shared capture service and improved case management.
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ibm, forrester, digital, engagement, forrester technology, information management, software development, it management, knowledge management, enterprise applications
    
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, enterprise applications
    
IBM
Published By: IBM     Published Date: Jul 08, 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, networking, software development, enterprise applications
    
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, data center
    
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, data management, data center
    
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 27, 2017
As with most innovations in business information technology, the ultimate truth about cloud lies somewhere in between. There is little doubt that cloud-based infrastructures offer an immediate opportunity for smaller organizations to avoid the costly investment needed for a robust on-premises computing environment. Data can be found, processed and managed on the cloud without investing in any local hardware. Large organizations with mature on-premises computing infrastructures are looking to Hadoop platforms to help them benefit from the vast array of structured and unstructured data from cloud-based sources. Organizations have feet in both cloud and on-premises worlds. In fact, one could easily argue that we already live in a “hybrid” world.
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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: Apr 03, 2017
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins. Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses. Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources
    
IBM
Published By: IBM     Published Date: Jun 29, 2018
LinuxONE from IBM is an example of a secure data-serving infrastructure platform that is designed to meet the requirements of current-gen as well as next-gen apps. IBM LinuxONE is ideal for firms that want the following: ? Extreme security: Firms that put data privacy and regulatory concerns at the top of their requirements list will find that LinuxONE comes built in with best-in-class security features such as EAL5+ isolation, crypto key protection, and a Secure Service Container framework. ? Uncompromised data-serving capabilities: LinuxONE is designed for structured and unstructured data consolidation and optimized for running modern relational and nonrelational databases. Firms can gain deep and timely insights from a "single source of truth." ? Unique balanced system architecture: The nondegrading performance and scaling capabilities of LinuxONE — thanks to a unique shared memory and vertical scale architecture — make it suitable for workloads such as databases and systems of reco
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IBM
Published By: IBM     Published Date: Jul 05, 2018
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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IBM
Published By: IBM     Published Date: Jul 09, 2018
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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IBM
Published By: IBM     Published Date: Jun 25, 2018
Vast resources of data are increasingly available, but the sheer volume can overwhelm human capability. By implementing the cognitive system of IBM Watson Discovery into their infrastructure, businesses can extract deeper and more accurate insights by efficiently identifying, collecting and curating structured and unstructured data. Watson Discovery, also capable of creating content collections and custom cognitive applications, can transform organizational processes to extend proprietary content and expert knowledge faster and at greater scales. Read more to learn how Watson Discovery can keep your organization evolving ahead of the competition. Click here to find out more about how embedding IBM technologies can accelerate your solutions’ time to market.
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IBM
Published By: IBM APAC     Published Date: Nov 22, 2017
It is imperative that organizations start looking now for smarter solutions to the problems associated with unstructured data. There are many issues related to unstructured data that need to be readily addressed such as storage, discovery, organization, tagging and deduplication. One of the most important issues related to unstructured data is finding and discovering key business insights as quickly as possible, preferably in near real time, to gain a significant competitive advantage.
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storage, discovery, organization, tagging, deduplication, competitive, advantage
    
IBM APAC
Published By: IBM APAC     Published Date: Mar 19, 2018
Unstructured data has exploded in volume over the past decade. Unstructured data, media files and other data can be created just about anywhere on the planet using almost any smart device available today. As the amount of unstructured data grows exponentially, customers using this data need to be able to take advantage of the right storage solutions to support all of their file and object data requirements. IBM® recently added a new storage system to their Spectrum product family, IBM Spectrum Network Attached Storage (NAS). IBM Spectrum NAS adds another software-defined file storage system to IBM’s current unstructured data storage solutions, IBM Spectrum Scale™ and IBM Cloud Object Storage (COS). Below, we will discuss the three systems and supply some guidance on when and where to use each of them.
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IBM APAC
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