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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
    
IBM
Published By: CrowdStrike     Published Date: Feb 01, 2017
One of the biggest challenges to effectively stopping breaches lies in sifting through vast amounts of data to find the subtle clues that indicate an attack is imminent or underway. As modern computer systems generate billions of events daily, the amount of data to analyze can reach petabytes. Compounding the problem, the data is often unstructured, discrete and disconnected. As a result, organizations struggle to determine how individual events may be connected to signal an impending attack. Download the white paper to learn: • How to detect known and unknown threats by applying high-volume graph-based technology, similar to the ones developed by Facebook and Google • How CrowdStrike solved this challenge by building its own proprietary graph data model • How CrowdStrike Threat Graph™ collects and analyzes massive volumes of security-related data to stop breaches
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CrowdStrike
Published By: Group M_IBM Q1'18     Published Date: Jan 04, 2018
IBM® InfoSphere® Big Match for Hadoop helps you analyze massive volumes of structured and unstructured customer data to gain deeper customer insights. It can enable fast, efficient linking of data from multiple sources to provide complete and accurate customer information—without the risks of moving data from source to source. The solution supports platforms running Apache Hadoop such as IBM Open Platform, IBM BigInsights, Hortonworks and Cloudera.
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hadoop, infosphere, data, customer insights
    
Group M_IBM Q1'18
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: Cloudian     Published Date: Feb 15, 2018
We are critically aware of the growth in stored data volumes putting pressure on IT budgets and services delivery. Burgeoning volumes of unstructured data commonly drive this ongoing trend. However, growth in database data can be expected as well as enterprises capture and analyze data from the myriad of wireless devices that are now being connected to the Internet. As a result, stored data growth will accelerate. Object-based storage systems are now available that demonstrate these characteristics. While they have a diverse set of use cases, we see several vendors now positioning them as on-premises targets for backups. In addition, integration of object-based data protection storage with cloud storage resources is seen by these vendors as a key enabler of performance at scale, cost savings, and administrative efficiency.
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Cloudian
Published By: Cloudian     Published Date: Feb 21, 2018
We are critically aware of the growth in stored data volumes putting pressure on IT budgets and services delivery. Burgeoning volumes of unstructured data commonly drive this ongoing trend. However, growth in database data can be expected as well as enterprises capture and analyze data from the myriad of wireless devices that are now being connected to the Internet. As a result, stored data growth will accelerate. Object-based storage systems are now available that demonstrate these characteristics. While they have a diverse set of use cases, we see several vendors now positioning them as on-premises targets for backups. In addition, integration of object-based data protection storage with cloud storage resources is seen by these vendors as a key enabler of performance at scale, cost savings, and administrative efficiency.
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Cloudian
Published By: Redstor UK     Published Date: May 02, 2018
Many organisations are facing challenges relating to the unstructured data they hold. By its very nature, unstructured data is in a form that is difficult to manage, and it is growing rapidly in size. This can make it difficult to understand who owns that data, whether it is being used or even whether it is of any value. Industry forecasts indicate the volume of data generated by corporates is expected to double over the next three years and, with General Data Protection Regulation taking effect in May 2018, organisations need a more efficient way to manage and control this data. This White Paper provides an overview of the important technical considerations senior business and IT management teams need to review before choosing an archiving provider.
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Redstor UK
Published By: Expert System     Published Date: Jul 26, 2019
As companies increasingly recognize the business implications and actionable benefits of AI, the question becomes: How will you use AI for your business? Thanks to the Cogito platform based on AI algorithms, organizations can effectively support and improve unstructured information management and text analytics in order to: Leverage all information, combining internal knowledge with other information sources to extract relevant data Provide effective and real-time insight on strategic initiatives, partners and any third parties Mitigate and even completely avoid risks for operations, reputation, etc. through information analysis and monitoring Know what competitors are doing and intercept market trends Implement automation for the broader, more complex set of processes that involve data Free up teams to focus on more creative or critical activities inside the organization See the entire business through a different perspective
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Expert System
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