data volume

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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: 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
    
VMWare - vFabric
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: 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: 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: Arbor     Published Date: Mar 13, 2014
All enterprises need to have mitigation solutions in place. Information security is vital in the workplace and DDoS has become more complex over time. Determine whether services are the best option for primary protection through this whitepaper.
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arbor, idc, distributed denial-of-service, ddos attack ddos solutions, dns reflection, exfiltration of data, security products, the cloud, cloud migration, high-bandwidth attacks, volumetric attacks, deployment, multi-vector threat, ips solutions, deployment models
    
Arbor
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: Oracle ZDLRA     Published Date: Jan 10, 2018
Traditional backup systems fail to meet the database protection and recovery requirements of modern organizations. These systems require ever-growing backup windows, negatively impact performance in mission-critical production databases, and deliver recovery time objectives (RTO) and recovery point objectives (RPO) measured in hours or even days, failing to meet the requirements of high-volume, high transactional databases -- potentially costing millions in lost productivity and revenue, regulatory penalties, and reputation damage due to an outage or data loss.
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data protection, backup speed, recovery, overhead, assurance, storage, efficiency, oracle
    
Oracle ZDLRA
Published By: CA Technologies_Business_Automation     Published Date: Jun 29, 2018
Challenge It is not uncommon for SAP system copies, including any post-editing, to take several days to complete. Meanwhile, testing, development and training activities come to a standstill, and the large number of manual tasks in the entire process ties up highly skilled SAP BASIS staff. Opportunity Enterprises are looking to automation as a way to accelerate SAP system copies and free up staff. However, this is only one part of the problem: What further complicates the system copy process is the need to safeguard sensitive data and manage huge data volumes while also ensuring that the data used in non-production systems adequately reflects the data in production systems so the quality of development, testing and training activities is not compromised. Benefits This white paper explains how a considerable portion of the SAP system copy process can be automated using the CA Automic Automated System Copy for SAP solution and SNP T-Bone, helping enterprises become more agile.
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CA Technologies_Business_Automation
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
    
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: IBM     Published Date: Oct 19, 2015
Read this new whitepaper to learn about the seven essential elements needed to achieve the highest performance
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ibm, performance, scalability, information, intgration, data volume, enterprise
    
IBM
Published By: IBM     Published Date: Oct 19, 2015
This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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ibm, integration, data volume, business technology, information
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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scalability, data warehousing, resource planning
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
To compete in today’s fast-paced business climate, enterprises need accurate and frequent sales and customer reports to make real-time operational decisions about pricing, merchandising and inventory management. They also require greater agility to respond to business events as they happen, and more visibility into business activities so information and systems are optimized for peak efficiency and performance. By making use of data capture and business intelligence to integrate and apply data across the enterprise, organizations can capitalize on emerging opportunities and build a competitive advantage. The IBM® data replication portfolio is designed to address these issues through a highly flexible one-stop shop for high-volume, robust, secure information replication across heterogeneous data stores. The portfolio leverages real-time data replication to support high availability, database migration, application consolidation, dynamic warehousing, master data management (MDM), service
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ibm, infosphere, data replication, security, data storage
    
IBM
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
Published By: HP - Enterprise     Published Date: Jun 04, 2013
Businesses are overwhelmed with data; it’s a blessing and a curse. A curse because it can overwhelm traditional approaches to storing and processing it. A blessing because the data promises business insight that never existed earlier. The industry has spawned a new term, “big data,” to describe it. Now, IT itself is overwhelmed with its own big data. In the press to roll out new services and technologies—mobility, cloud, virtualization—applications, networks, and physical and virtual servers grow in a sprawl. With them comes an unprecedented volume of data such as logs, events, and flows. It takes too much time and resources to sift through it, so most of it lies unexplored and unexploited. Yet like business data, it contains insight that can help us solve problems, make decisions, and plan for the future.
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data research, big data, virtualization, applications, networks
    
HP - Enterprise
Published By: NetApp     Published Date: Nov 13, 2017
To help member hospitals and clinics easily, securely, and affordably protect expanding data volumes, Engage switched to NetApp® AltaVault backup.
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NetApp
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: Datastax     Published Date: Dec 27, 2018
Today’s data volume, variety, and velocity has made relational database nearly obsolete for handling certain types of workloads. But it’s also put incredible strain on regular NoSQL databases. The key is to find one that can deliver the infinite scale and high availability required to support high volume, web-scale applications in clustered environments. This white paper details the capabilities and uses case of an Active Everywhere database
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Datastax
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
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