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Published By: Denodo     Published Date: Mar 01, 2019
With the advent of big data and the proliferation of multiple information channels, organizations must store, discover, access, and share massive volumes of traditional and new data sources. Data virtualization transcends the limitations of traditional data integration techniques such as ETL by delivering a simplified, unified, and integrated view of trusted business data. Learn how you can: • Conquer siloed data in the enterprise • Integrate all data sources and types • Cope with regulatory requirements • Deliver big data solutions that work • Take the pain out of cloud adoption • Drive digital transformation
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Denodo
Published By: DATAVERSITY     Published Date: Jul 24, 2014
Will the “programmable era” of computers be replaced by Cognitive Computing systems which can learn from interactions and reason through dynamic experience just like humans? With rapidly increasing volumes of Big Data, there is a compelling need for smarter machines to organize data faster, make better sense of it, discover insights, then learn, adapt, and improve over time without direct programming. This paper is sponsored by: Cognitive Scale.
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data, data management, cognitive computing, machine learning, artificial intelligence, research paper
    
DATAVERSITY
Published By: MarkLogic     Published Date: Jun 17, 2015
Modern enterprises face increasing pressure to deliver business value through technological innovation that leverages all available data. At the same time, those enterprises need to reduce expenses to stay competitive, deliver results faster to respond to market demands, use real-time analytics so users can make informed decisions, and develop new applications with enhanced developer productivity. All of these factors put big data at the top of the agenda. Unfortunately, the promise of big data has often failed to deliver. With the growing volumes of unstructured and multi-structured data flooding into our data centers, the relational databases that enterprises have relied on for the last 40-years are now too limiting and inflexible. New-generation NoSQL (“Not Only SQL”) databases have gained popularity because they are ideally suited to deal with the volume, velocity, and variety of data that businesses and governments handle today.
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data, data management, databse, marklogic, column store, wide column store, nosql
    
MarkLogic
Published By: MapR Technologies     Published Date: Mar 29, 2016
Add Big Data Technologies to Get More Value from Your Stack Taking advantage of big data starts with understanding how to optimize and augment your existing infrastructure. Relational databases have endured for a reason – they fit well with the types of data that organizations use to run their business. These types of data in business applications such as ERP, CRM, EPM, etc., are not fundamentally changing, which suggests that relational databases will continue to play a foundational role in enterprise architectures for the foreseeable future. One area where emerging technologies can complement relational database technologies is big data. With the rapidly growing volumes of data, along with the many new sources of data, organizations look for ways to relieve pressure from their existing systems. That’s where Hadoop and NoSQL come in.
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MapR Technologies
Published By: Splice Machine     Published Date: Nov 16, 2014
Organizations are now looking for ways to handle exploding data volumes while reducing costs and maintaining performance. Managing large volumes and achieving high levels of concurrency on traditional scale up databases, such as Oracle, often means purchasing expensive scale-up hardware. In this white paper, learn about the different options and benefits of scale out solutions for Oracle database users.
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splice machine, oracle, oracle database, database, hadoop, nosql, white paper, data, data management, dataversity
    
Splice Machine
Published By: Basho     Published Date: Sep 30, 2016
The Internet of Things (IoT) or the Internet of Everything is changing the way companies interact with their customers and manage their data. These connected devices generate high volume time series data that can be created in milliseconds. This fast growth of IoT data and other time series data is producing challenges for enterprise applications where data must be collected, saved, and analyzed in the blink of an eye. Your application needs a database built to uniquely handle time series data to ensure your data is continuously available and accurate.Learn about the only NoSQL database optimized for IoT and Time Series data in this technical overview. Riak TS stores and analyzes massive amounts of data and is designed to be faster than Cassandra.
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Basho
Published By: Finch Computing     Published Date: Apr 26, 2016
FinchDB is not just a database, not just an analytics engine and not just a search tool. It’s all three. All together. All in-memory. It’s a new, enabling platform technology built on an IP portfolio of 25 unique inventions, and suited for multiple high-volume, high-stakes use cases. While other big data solutions are answers-oriented, FinchDB enables users to ask better questions of their data. Because better questions must come before better answers.
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Finch Computing
Published By: CloverETL     Published Date: Nov 24, 2017
The volume of data is increasing by 40% per year (Source: IDC). In addition, the structure and quality of data differs vastly with a growing number of data sources. More agile ways of working with data are required. This whitepaper discusses the vast options available for managing and storing data using data architectures, and offers use cases for each architecture. Furthermore, the whitepaper explores the benefits, drawbacks and challenges of each data architecture and commonly used practices for building these architectures.
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CloverETL
Published By: Syncsort     Published Date: Jan 04, 2018
The term Big Data doesn’t seem quite “big enough” anymore to properly describe the vast over-abundance of data available to organizations today. As the volume and variety of Big Data sources continue to grow, the level of trust in that data remains troublingly low. Read on and discover how a strong focus on data quality spanning the people, processes and technology of your organization will help keep your data lake pristine.
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Syncsort
Published By: Denodo     Published Date: Feb 07, 2019
With the advent of big data and the proliferation of multiple information channels, organizations must store, discover, access, and share massive volumes of traditional and new data sources. Data virtualization transcends the limitations of traditional data integration techniques such as ETL by delivering a simplified, unified, and integrated view of trusted business data. Learn how you can: • Conquer siloed data in the enterprise • Integrate all data sources and types • Cope with regulatory requirements • Deliver big data solutions that work • Take the pain out of cloud adoption • Drive digital transformation
Tags : 
    
Denodo
Published By: MarkLogic     Published Date: Sep 01, 2015
Organizations face a growing inability to handle the massive volumes of disparate, varied, and changing data with the relational databases that have been relied on for the past three decades. This white paper provides a detailed discussion of the key reasons why relational databases are ill-suited to address the challenges with today’s data, and an overview of how new kinds of databases solve those challenges.
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MarkLogic
Published By: Building Engines     Published Date: Mar 18, 2019
The volume of technology solutions available to CRE professionals is tremendous, and new entrants are emerging at a faster pace than ever. To succeed in this environment, highly effective CRE organizations behave differently than their peers in how they approach, select, and adopt technology. For CRE professionals seeking to develop a more technologically mature organization, the findings in this report provide a few clear guidelines.
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Building Engines
Published By: Nuance     Published Date: Feb 09, 2012
Using your desired number of seats, we have compared Adobe Acrobat Stardard CPL/TLP published pricing to Nuance volume pricing. Download this calculator to see how much you can save with Nuance PDF Converter Enterprise.
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analytical applications
    
Nuance
Published By: Zebra Technologies     Published Date: Mar 19, 2019
KEEP YOUR TEAMS MOVING AND PATIENTS SAFER More and more patients are turning to Ambulatory Surgery Centers (ASC) for outpatient surgeries, diagnostic testing and preventive procedures. Case volumes continue to rise and competition for patients is intensifying. At the same time, reimbursement rates are declining. How are ASCs thriving in this rapidly-changing climate? By incorporating sophisticated data capture solutions throughout the patient journey, ASCs are enhancing patient safety, improving clinical work flows and reducing overall costs.
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Zebra Technologies
Published By: Dependable Solutions     Published Date: Feb 16, 2010
A critical challenge for many companies in 2009 was to stay on top of licensees' obligations, payments, receipts and royalties, along with growing volume of approvals.
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dependable solutions, licensing, edi, electronic data interchange, sku
    
Dependable Solutions
Published By: SAP     Published Date: Feb 03, 2017
In the digital economy, data is becoming more interconnected every day. The volume of highly-connected data is growing rapidly, while also becoming a highly-valued corporate asset. By exploring relationships among people, processes and things, new business opportunities emerge, helping grow your business's competitive advantage.
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SAP
Published By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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Cisco
Published By: HERE Technologies     Published Date: Jan 22, 2019
To improve safety and mobility across its 5,600km road network, the City of Toronto forged a partnered with HERE Technologies for the provision of traffic, incident, and historical traffic data. Access to this data allows the city authority to see exactly what’s happening on its roads and more easily and affectively run studies on improvement projects. This case study details how HERE Technologies enabled the City of Toronto’s transportation team to: Work smarter with comprehensive network coverage and accurate data to aid analysis Examine the impact of city projects without significant forward planning or expenditure Ensure travel volume models used to drive decision making are calibrated to represent real-world truths
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public sector, urbanization, traffic management
    
HERE Technologies
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
For the typical enterprise, the volume of data that needs to be managed and protected is growing at roughly 40% per year. Add to that the performance requirements of new applications and the demands for instant response time, always-on availability, and anytime-anywhere access. With such demands, data center managers face storage challenges that cannot be addressed using traditional, spinning-disk technology.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
Pour une entreprise type, le volume de données devant être gérées et protégées augmente d'environ 40 % par an. Ajoutez à cela les exigences de performances des nouvelles applications, de temps de réponse instantanés, de disponibilité continue et d'accès en tout lieu et en tout temps. Avec de telles exigences, les responsables des datacenters sont confrontés à des défis de stockage qui ne peuvent pas être relevés à l'aide de technologies de disques rotatifs traditionnelles.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
In einem typischen Unternehmen steigt das Datenvolumen, das verwaltet und geschützt werden muss, um ca. 40 % pro Jahr. Dazu kommen die Performanceanforderungen neuer Anwendungen und der Wunsch nach kurzen Antwortzeiten, ständiger Verfügbarkeit und Zugri zu jeder Zeit und an jedem Ort. Diese Speicheranforderungen lassen sich nicht mit herkömmlicher Technik mit rotierenden Festplatten bewältigen.
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Hewlett Packard Enterprise
Published By: Dell     Published Date: Nov 02, 2018
When it comes to effectively and efficiently protecting growing volumes of data, midsized organizations face unique challenges. That is because they live in a world of constraints that are both operational and budgetary in nature. Cloud disaster recovery offers new options for these organizations—they can optimize their data protection economics by integrating on-premises protection solutions with cloud-based backup and recovery methods. Dell EMC’s cloud-ready solutions, particularly its Integrated Data Protection Appliances with native cloud extension capabilities, along with its Data Protection Software working in conjunction with its Data Domain backup storage appliances, provide cloud disaster recovery with flexible features. These solutions enhance operational efficiency and provide midsized organizations with clear economic and operational benefits.
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Dell
Published By: Hewlett Packard Enterprise     Published Date: Oct 24, 2017
Big Data is not just a big buzzword. Government agencies have been collecting large amounts of data for some time and analyzing the data collected to one degree or another. Big data is a term that describes high volume, variety and velocity of information that inundates an organization on a regular basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and better services.
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cloud optimization, cloud efficiency, cloud management, cloud assurance, cloud visibility, enterprise management, data management
    
Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Mar 26, 2018
Modern storage arrays can’t compete on price without a range of data reduction technologies that help reduce the overall total cost of ownership of external storage. Unfortunately, there is no one single data reduction technology that fits all data types and we see savings being made with both data deduplication and compression, depending on the workload. Typically, OLTP-type data (databases) work well with compression and can achieve between 2:1 and 3:1 reduction, depending on the data itself. Deduplication works well with large volumes of repeated data like virtual machines or virtual desktops, where many instances or images are based off a similar “gold” master.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Jul 19, 2018
The next wave of cloud storage innovation is upon us. It’s called multicloud. With multicloud storage you can combine cloud simplicity with enterprise-grade reliability, provide data mobility among multiple cloud types, and eliminate vendor lock-in. And it’s available right now through the Nimble Cloud Volumes service.
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cloud, storage, flash
    
Hewlett Packard Enterprise
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