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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: HP Inc.     Published Date: Jun 20, 2019
Four billion people now generate four quintillion bytes of data every day - and with the number of IoT devices set to increase to three times the global population by 2022 - volumes will only continue to rise. The challenge is processing the data. This is why machine learning, deep learning and all the other developing forms of AI must deliver the analytics toolset businesses need to compete.
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HP 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: Intel     Published Date: Sep 25, 2019
Distributed cloud architectures will play an important role in Communication Service Providers’ network transformations. The distributed cloud will be made of numerous edge locations, from the customer premises to mobile base stations to central offices, each of which has its benefits and constraints. CSPs will need to consider attributes such as performance, availability, security, integration, and data and traffic volume to optimize the infrastructure for a myriad of workloads. Learn more about Heavy Reading’s survey results on CSPs adopting a distributed cloud strategy and delivering new services in this white paper.
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Intel
Published By: Oracle     Published Date: Oct 20, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make bette
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make bette
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical. These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most compani
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Oracle
Published By: Red Hat, Inc.     Published Date: Jul 12, 2012
Recently, enterprises have seen enormous gains in scalability, flexibility, and affordability as they migrated from proprietary, monolithic server architectures to architectures that are virtualized, open source, standardized, and commoditized.
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scalability, flexibility, affordability, performance, ease-of-use, reduced acqisition costs, reduced maintenance costs, red hat storage server
    
Red Hat, Inc.
Published By: Cisco     Published Date: Aug 27, 2015
This whitepaper talks about the development and adoption of the (IoT) and how much of a critical element it is for smarter manufacturing.
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smarter manufacturing, data research, inter of things, iot, customer satisfaction, big data, programmable logic controllers, supply chain logistics
    
Cisco
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
    
Lucidworks
Published By: HP Inc.     Published Date: Feb 14, 2019
How to overcome complexity and be ready for future growth. The modern production digital print market brought a world of opportunities for micro-runs and variable data printing into the hands of Print Service Providers (PSPs). With print available in any quantity to anyone, print is being democratized, resulting in ever-greater numbers of increasingly smaller jobs. The old print model of high-volume static print is being replaced with a myriad of micro-runs and micro-jobs. Automation that allows PSP owners to master the ensuing complexity and respond faster than ever before is enabling them to refocus on market development and on delivering value.
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HP Inc.
Published By: Gemini Data     Published Date: Jan 16, 2018
The increasing reliance on big data platforms for all functions of the organization has been transformative. As these environments mature and data volumes increase, organizations face infrastructure and management scalability challenges. Gemini Enterprise Manager simplifies deployment and management with a turnkey, NoOps appliance, providing simplicity, security, and speed to accelerate the time to value for any analysis use case. Manager allows you to control your Splunk deployment as a single, unified solution deployed on premises, in the cloud or both.
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Gemini Data
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: QlikTech     Published Date: Aug 27, 2013
There is an incredible amount of interest in the topic of Big Data at present: for some organisations its use is an operational reality, providing unprecedented ability to store and analyse large volumes of disparate data that are critical to the organization’s competitive success. It has enabled people to identify new opportunities and solve problems they haven’t been able to solve before. Download this whitepaper to learn more.
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big data, qlikview, big data solutions, opportunity, business opportunity, competitive success, store, analyse
    
QlikTech
Published By: Dell     Published Date: Sep 12, 2013
Information is the engine of business growth in the digital age. Market intelligence, customer information, intellectual property and other data can be harnessed to create a quantifiable competitive advantage for a company and lay the path for future expansion. Yet as critical as data can be, the sweeping year-over-year proliferation in data volumes can quickly overwhelm an IT organization. This is much more than a budget problem: Without an effective data storage strategy, an organization is putting a critical resource at risk.
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data storage management, microsoft windows server, market intelligence, customer information, intellectual property, data, it organizations, storage strategy
    
Dell
Published By: Dell EMC     Published Date: Mar 18, 2016
Big Data brings unquestionable value to any organization. But as it continues to grow in volume, more sources and increased storage capacity needs grow with it, taxing the performance of existing infrastructures. But you don’t have to be stuck in such a dismal place. Make the trip to Data Lake instead.
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emc, data lake, big data, storage, infrastructure
    
Dell EMC
Published By: AWS     Published Date: Nov 02, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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AWS
Published By: Cloudian     Published Date: Feb 20, 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.
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Cloudian
Published By: Cohesity     Published Date: Aug 09, 2019
The growing importance—and complexity—of data protection means old approaches no longer will get the job done in an era of exploding data volumes and ever-changing business requirements. It’s time to reimagine and reengineer your IT infrastructure for a more efficient, affordable and manageable data protection framework.
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Cohesity
Published By: EverString     Published Date: Jul 27, 2018
You have lots of leads, but finding the right match is getting harder and harder. You know the good leads are out there. They might even be looking for you. The trouble is, those good leads are hidden among so many bad ones. Your sales and marketing teams know this. They’re facing a deluge of data, not all of it reliable, and they’re trying to decode that data using outdated point solutions and imperfect criteria. Which means a lot of time spent running campaigns, initiating conversations and booking meetings that go nowhere. If this were the dating world, we’d be talking about a calendar full of bad first dates. Everyone’s “swiping right,” but no one’s truly matching. No one’s getting a second date. No one’s committing. Something just isn’t working. We can’t help you if you’re dating. But if you’re trying to sell your company’s products and services—well, the game is about to change. Instead of moving through a volume of potential customers as quickly as possible to build pipeline, th
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EverString
Published By: Talend     Published Date: Nov 02, 2018
Siloed data sources, duplicate entries, data breach risk—how can you scale data quality for ingestion and transformation at big data volumes? Data and analytics capabilities are firmly at the top of CEOs’ investment priorities. Whether you need to make the case for data quality to your c-level or you are responsible for implementing it, the Definitive Guide to Data Quality can help. Download the Definitive Guide to learn how to: Stop bad data before it enters your system Create systems and workflow to manage clean data ingestion and transformation at scale Make the case for the right data quality tools for business insight
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Talend
Published By: SRC,LLC     Published Date: Jun 01, 2009
Today, organizations are collecting data at every level of their business and in volumes that in the past were unimaginable. Data sets are stored in different database systems or in files with distinctive formats, all reflecting business process, application, program software, or information type dependencies. Adding to this complexity is the distribution of these data sets across the enterprise in silos requiring a varied set of tools and/or specialized business rules for data transformation, classification, matching, and integration. Because of the massive amounts of data stored in a variety of representation formats, decision makers strain to derive insights and create business solutions that adequately span and integrate information from these disparate technology islands. Learn more today!
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src, data transformation, classification, business value, geographic business intelligence, geo-bi, etl, extract
    
SRC,LLC
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
    
iKnowtion
Published By: IBM     Published Date: Aug 08, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media.
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big data, analytics, insurance, customer service, solutions
    
IBM
Published By: IBM     Published Date: Aug 08, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media.
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big data, analytics, insurance, customer service, solutions
    
IBM
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