data volume

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Published By: IBM     Published Date: Nov 08, 2017
Flexible deployment options, licensing models help take the challenges out of change. As you move toward the cloud, you're likely planning or managing a mixed environment of on- premises and on- cloud applications. To help you succeed in this transition, you need a trans-formative, mixed-workload database that can handle a massive volume of data while delivering high performance, data availability and the flexibility to adapt respond to business changes.
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ibm db2, cloud, on-cloud applications, mixed-workload database
    
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 05, 2018
Scalable data platforms such as Apache Hadoop offer unparalleled cost benefits and analytical opportunities. IBM helps fully leverage the scale and promise of Hadoop, enabling better results for critical projects and key analytics initiatives. The end-to- end information capabilities of IBM® Information Server let you better understand data and cleanse, monitor, transform and deliver it. IBM also helps bridge the gap between business and IT with improved collaboration. By using Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of- impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time. Since its inception, Information Server has been a massively parallel processing (MPP) platform able to support everything from small to very large data volumes to meet your requirements, regardless of complexity. Information Server can uniquely support th
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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: Jul 09, 2017
Organizations today collect a tremendous amount of data and are bolstering their analytics capabilities to generate new, data-driven insights from this expanding resource. To make the most of growing data volumes, they need to provide rapid access to data across the enterprise. At the same time, they need efficient and workable ways to store and manage data over the long term. A governed data lake approach offers an opportunity to manage these challenges. Download this white paper to find out more.
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data lake, big data, analytics
    
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
Published By: IBM APAC     Published Date: Jul 19, 2019
With businesses developing larger data volumes to improve their competitiveness, their IT infrastructures are struggling to store and manage all of the data. To keep pace with this increase in data, organizations require a modern enterprise storage infrastructure that can scale to meet the demands of large data sets, while reducing the cost and complexity of infrastructure management. This white paper examines IBM’s FlashSystem 9100 solution and the benefits it can offer businesses.
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IBM APAC
Published By: IBM APAC     Published Date: Jul 19, 2019
Requirements for secure, long-term data retention are common and increasingly stringent, with data volumes growing massively as a result. Tape storage offers a less costly long-term storage option than disk drives or flash. And, data stored on tape kept offline, or on write-once media, is nearly invulnerable to hacking. This white paper looks at the benefits that IBM TS4300 Tape Library can provide businesses.
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IBM APAC
Published By: IBM Watson Health     Published Date: Dec 10, 2018
In this case study, large health systems implement IBM Watson Health to surface improvement opportunities. Using this tool, they were able to cut costs, reduce patients’ length of stay, acquire actionable data, address number of readmissions and improve management of COPD and sepsis.
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hospitals, health systems, healthcare, analytics, data, insights, case study, performance improvement, healthcare insights, cost, length of stay, financial performance data, readmissions, quality performance, benchmarks, dashboards, patient volume, savings
    
IBM Watson Health
Published By: iKnowtion     Published Date: Nov 09, 2011
iKnowtion helped this data-rich, US automotive manufacturer by developing a test and learn strategy that identified new areas for sales volume growth, while learning how to market more strategically to its customer base.
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crm strategies, test and learn, marketing strategies, customer base, analytics, iknowtion, automotive, crm solutions/software, customer experience/engagement, business intelligence, market research, usability
    
iKnowtion
Published By: Intel     Published Date: Apr 16, 2019
The data center is coming under immense pressure. The boom in connected devices means increasing volumes of data – and all that needs processing. One way for CSPs to accelerate customer workloads is by using FPGAs, which are easier to use than ever before. Download Intel's latest eGuide, ‘FPGA-as-a-Service: A Guide for CSPs' to discover: • How to add FPGAs to the data center • The structure of the Intel® Acceleration Stack for FPGAs • Adding off-the-shelf accelerator functions • How FPGAs can accelerate many cloud services, such as database as a service and analytics as a service
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Intel
Published By: JBoss Developer     Published Date: Jan 25, 2016
The ability to integrate systems and share data across the enterprise is a common datacenter need. The needs of an integration bus, the technology used for middleware-based integration, can varyin complexity, data volume, and required performance. Both Red Hat and MuleSoft offer multiple products that can help customers develop and deploy middleware integration solutions. This competitive overview compares Red Hat® JBoss® Fuse to Mule ESB Enterprise.
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red hat jboss fuse, middleware-based integrations, data volume, integration performance, soa, integration solutions, open source licensing
    
JBoss Developer
Published By: Juniper Networks     Published Date: Aug 03, 2017
Security, network complexity and growing volumes of traffic are the top factors affecting enterprise network strategy, based on a recent IDG Research Services poll among IT leaders. Here’s what they’re planning to do about these issues
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information technology, data security, network complexity, traffic volume, network strategy
    
Juniper Networks
Published By: K2     Published Date: Apr 27, 2015
This paper describes how a business-app platform from K2® can help you provide simpler, more cost-effective ways to empower people by connecting them with data that is dispersed across different systems.
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erp and legacy systems, data volume, business processes, cloud crm system, system complexity, business apps
    
K2
Published By: Layered Tech, Inc.     Published Date: Dec 16, 2010
Layered Tech's engineers created a customized package of virtual private data centers (VPDCs), managed services and disaster recovery solutions that support KANA's clients, large and small. Layered Tech tailored the architecture to meet the highest enterprise security requirements, as well as ensuring that each KANA client can deploy applications that scale to ongoing volume fluctuations.
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layered tech, kana, virtual private data center, enterprise security, vpdc, disaster recovery, customer interaction
    
Layered Tech, Inc.
Published By: LogMeIn     Published Date: Feb 27, 2018
24/7 Self-Service Support Center: Bold360 ai’s 24/7 context driven support center was implemented, allowing users to instantly discover relevant content from the smart knowledge database. Dynamic FAQs displayed trending topics in real-time to speed up customer resolution and discoverability. Real-Time Customer Analytics highlight unanswered questions, giving Premium Credit instant visibility of missing topics, questions driving ticket volume, and more.
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customer, support, faq, credit
    
LogMeIn
Published By: Lucidworks     Published Date: Feb 12, 2015
Search is all your data, all the time, at scale. Read this white paper today and learn about Lucidworks Fusion, the next-generation search platform built on Apache Solr.
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search platform, search query, search technologies, big data, high-volume data, database advancements
    
Lucidworks
Published By: Lucidworks     Published Date: Jun 24, 2015
Using content, context, and the crowd to build better search applications.
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search platform, search query, search technologies, big data, high-volume data, database advancements, it management, knowledge management, platforms, data management, intent, context
    
Lucidworks
Published By: Lucidworks     Published Date: Aug 24, 2016
In reality, we developed search technologies, not primarily as a front-end service but to alleviate the challenges of the back end: our data. Search grew in direct response to data problems. The search story can’t be told without the data story, and high-volume data would be nearly useless without search technology. Download this eBook to learn more about search technologies.
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search, search query, search technologies, search apps, data problems, ecommerce search
    
Lucidworks
Published By: MalwareBytes EMEA     Published Date: May 10, 2019
Enterprises, beware. Threat actors are continuing to eye businesses for high returns on investment in Q1 2019, breaching infrastructure, exfiltrating or holding data hostage, and abusing weak credentials for continued, targeted monitoring. From a steadfast increase of pervasive Trojans, such as Emotet, to a resurgence of ransomware lodged against corporate targets, cybercriminals are going after organizations with a vengeance. Yet every cloud has a silver lining, and for all the additional effort thrown at businesses, consumer threats are now on the decline. Ransomware against consumers has slowed down to a trickle and cryptomining, at a fever pitch against consumers this time last year, has all but died. Interestingly, this has resulted in an overall decline in the volume of malware detections from Q4 2018 to Q1 2019. While threat actors made themselves busy with challenging new victims, they ensnared targets in the old ways, using tried-and-true malspam and social engineering tactic
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MalwareBytes EMEA
Published By: MarkLogic     Published Date: Mar 13, 2015
Big Data has been in the spotlight recently, as businesses seek to leverage their untapped information resources and win big on the promise of big data. However, the problem with big data initiatives are that organizations try using existing information management practices and legacy relational database technologies, which often collapse under the sheer weight of the data. In this paper, MarkLogic explains how a new approach is needed to handle the volume, velocity, and variety of big data because the current relational model that has been the status quo is not working. Learn about the NoSQL paradigm shift, and why NoSQL is gaining significant market traction because it solves the fundamental challenges of big data, achieving better performance, scalability, and flexibility. Learn how MarkLogic’s customers are reimagining their data to: - Make the world more secure - Provide access to valuable information - Create new revenue streams - Gain insights to increase market share - Reduce b
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enterprise, nosql, relational, databases, data storage, management system, application, scalable
    
MarkLogic
Published By: MarkLogic     Published Date: Jun 09, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic
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MarkLogic
Published By: MarkLogic     Published Date: Nov 07, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic.
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MarkLogic
Published By: MarkLogic     Published Date: Mar 29, 2018
Real World Evidence (RWE) requires the correlation of complex, frequently changing, unstructured data. To the enterprise architect, that means extracting value from data that doesn't neatly fit solutions. In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that is required to be successful with RWE. It is for this reason that leading life science organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic.
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data, integration, volume, optimization, architect, enterprise
    
MarkLogic
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