data volumes

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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: Akamai Technologies     Published Date: Apr 25, 2018
Cyber attackers are targeting the application programming interfaces (APIs) used by businesses to share data with customers. Consumer mobile adoption, electronic goods and services, and high volumes of data have led businesses to use APIs for data exchange. Unfortunately, attackers can also use APIs to access or deny service to valuable data and systems. This white paper explores strategies for protecting APIs. You’ll learn about APIs, how and why these endpoints are targets for web application attacks, security models, and how Akamai can help.
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api, security, interface, businesses, data, mobile, adoption
    
Akamai Technologies
Published By: Akamai Technologies     Published Date: Apr 25, 2018
Cyber attackers are targeting the application programming interfaces (APIs) used by businesses to share data with customers. Consumer mobile adoption, electronic goods and services, and high volumes of data have led businesses to use APIs for data exchange. Unfortunately, attackers can also use APIs to access or deny service to valuable data and systems. This white paper explores strategies for protecting APIs. You’ll learn about APIs, how and why these endpoints are targets for web application attacks, security models, and how Akamai can help.
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api, security, interface, businesses, data, mobile, adoption
    
Akamai Technologies
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
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: Oracle     Published Date: Nov 28, 2017
Today’s leading-edge organizations differentiate themselves through analytics to further their competitive advantage by extracting value from all their data sources. Other companies are looking to become data-driven through the modernization of their data management deployments. These strategies do include challenges, such as the management of large growing volumes of data. Today’s digital world is already creating data at an explosive rate, and the next wave is on the horizon, driven by the emergence of IoT data sources. The physical data warehouses of the past were great for collecting data from across the enterprise for analysis, but the storage and compute resources needed to support them are not able to keep pace with the explosive growth. In addition, the manual cumbersome task of patch, update, upgrade poses risks to data due to human errors. To reduce risks, costs, complexity, and time to value, many organizations are taking their data warehouses to the cloud. Whether hosted lo
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Oracle
Published By: Oracle CX     Published Date: Oct 19, 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 better
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Oracle CX
Published By: Oracle CX     Published Date: Oct 19, 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 better
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Oracle CX
Published By: Oracle CX     Published Date: Oct 19, 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 companies
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Oracle CX
Published By: Dell EMC     Published Date: Nov 10, 2015
From your most critical workloads to your cold data, a scale-out or scale-up storage solution — one that can automatically tier volumes or data to the most appropriate arrays or media (flash SSDs or HDDs) and offers advanced software features to help ensure availability and reliability — can help you efficiently manage your data center.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
To compete in this new multi-channel environment, we’ve seen in this guide how retailers have to adopt new and innovative strategies to attract and retain customers. Big data technologies, specifically Hadoop, enable retailers to connect with customers through multiple channels at an entirely new level by harnessing the vast volumes of new data available today. Hadoop helps retailers store, transform, integrate and analyze a wide variety of online and offline customer data—POS transactions, e-commerce transactions, clickstream data, email, social media, sensor data and call center records—all in one central repository.
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Dell EMC
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: Akamai Technologies     Published Date: Apr 25, 2018
Cyber attackers are targeting the application programming interfaces (APIs) used by businesses to share data with customers. Consumer mobile adoption, electronic goods and services, and high volumes of data have led businesses to use APIs for data exchange. Unfortunately, attackers can also use APIs to access or deny service to valuable data and systems. This white paper explores strategies for protecting APIs. You’ll learn about APIs, how and why these endpoints are targets for web application attacks, security models, and how Akamai can help.
Tags : 
api, security, interface, businesses, data, mobile, adoption
    
Akamai Technologies
Published By: Akamai Technologies     Published Date: Apr 13, 2018
Cyber attackers are targeting the application programming interfaces (APIs) used by businesses to share data with customers. Consumer mobile adoption, electronic goods and services, and high volumes of data have led businesses to use APIs for data exchange. Unfortunately, attackers can also use APIs to access or deny service to valuable data and systems. This white paper explores strategies for protecting APIs. You’ll learn about APIs, how and why these endpoints are targets for web application attacks, security models, and how Akamai can help.
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api, security, interface, businesses, data, mobile, adoption
    
Akamai Technologies
Published By: VMWare - vFabric     Published Date: May 10, 2012
View this webcast to learn how to achieve real-time awareness by managing ever-increasing data volumes and transaction rates.
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vfabric, vmware virtualization, server virtualization, desktop virtualization, public cloud, private cloud, virtual machine, vmware, vm ware, regulations, risk assessment, data management, data integration, data mining, information management, virtualization, cloud computing, infrastructure
    
VMWare - vFabric
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: Dell PC Lifecycle     Published Date: Mar 09, 2018
Compression algorithms reduce the number of bits needed to represent a set of data—the higher the compression ratio, the more space this particular data reduction technique saves. During our OLTP test, the Unity array achieved a compression ratio of 3.2-to-1 on the database volumes, whereas the 3PAR array averaged a 1.3-to-1 ratio. In our data mart loading test, the 3PAR achieved a ratio of 1.4-to-1 on the database volumes, whereas the Unity array got 1.3 to 1.
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Dell PC Lifecycle
Published By: Dell PC Lifecycle     Published Date: Mar 09, 2018
Les algorithmes de compression réduisent le nombre de bits nécessaires pour représenter un ensemble de données. Plus le taux de compression est élevé, plus cette technique de réduction des données permet d’économiser de l’espace. Lors de notre test OLTP, la baie Unity a atteint un taux de compression de 3,2 pour 1 sur les volumes de base de données. De son côté, la baie 3PAR affichait en moyenne un taux de 1,3 pour 1. Sur le test de chargement DataMart, la baie 3PAR a atteint un taux de 1,4 pour 1 sur les volumes de bases de données, tandis que la baie Unity enregistrait un taux de 1,3 pour 1.
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Dell PC Lifecycle
Published By: Riverbed     Published Date: May 24, 2012
Data transfer bottlenecks and unpredictability on the Wide Area Network (WAN) can hurt application performance. In addition, the time required to migrate large volumes of data to and from data centers can be a serious concern to business continuity.
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wan, wan optimization, riverbed, virtual steelhead, business technology, data center
    
Riverbed
Published By: Dell & Microsoft     Published Date: Aug 14, 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 & Microsoft
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 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.
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Oracle PaaS/IaaS/Hardware
Published By: CA Mainframe     Published Date: Sep 12, 2008
Increasing infrastructure complexity has led to unprecedented growth in enterprise systems management data on all systems, including the mainframe and it is becoming more complex to manage SMF data.  Download this Technology Brief to learn how to address the complexity of managing SMF data.
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smf, service management, data management, infrastructure, systems management, ca mainframe, mainframe
    
CA Mainframe
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