enterprise analytics

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By: NetApp     Published Date: Dec 13, 2013
FlexPod Select with Hadoop delivers enterprise class Hadoop with validated, pre-configured components for fast deployment, higher reliability and smoother integration with existing applications and infrastructure.  These technical reference architectures optimize storage, networking, and servers with Cloudera and Hortonworks distributions of Hadoop. Leverage FlexPod Select with Hadoop to help store, manage, process and perform advanced analytics on your multi-structured data.   Tuning parameters, optimization techniques among other Hadoop cluster guidelines  are provided.
Tags : flexpod with hadoop, enterprise data, storage infrastructure, massive amounts of data
     NetApp
By: NetApp     Published Date: Dec 13, 2013
Interested in running a Hadoop proof of concept on enterprise-class storage? Download this solutions guide to get a technical overview on building Hadoop on NetApp E-series storage. NetApp Open Solution for Hadoop delivers big analytics with preengineered, compatible, and supported solutions based on high-quality storage platforms so you reduce the cost, schedule, and risk of do-it-yourself systems and relieving the skills gap most organizations have with Hadoop. See how on going operational and maintenance costs can be reduced with a high available and scalable Hadoop solution.
Tags : open solutions, hadoop solutions guide
     NetApp
By: IBM     Published Date: May 20, 2015
According to our global study of more than 800 cloud decision makers and users are becoming increasingly focused on the business value cloud provides. Cloud is integral to mobile, social and analytics initiatives – and the big data management challenge that often comes with them and it helps power the entire suite of game-changing technologies. Enterprises can aim higher when these deployments are riding on the cloud. Mobile, analytics and social implementations can be bigger, bolder and drive greater impact when backed by scalable infrastructure. In addition to scale, cloud can provide integration, gluing the individual technologies into more cohesive solutions. Learn how companies are gaining a competitive advanatge with cloud computing.
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     IBM
By: Storiant     Published Date: Mar 16, 2015
Read this new IDC Report about how today's enterprise datacenters are dealing with new challenges that are far more demanding than ever before. Foremost is the exponential growth of data, most of it unstructured data. Big data and analytics implementations are also quickly becoming a strategic priority in many enterprises, demanding online access to more data, which is retained for longer periods of time. Legacy storage solutions with fixed design characteristics and a cost structure that doesn't scale are proving to be ill-suited for these new needs. This Technology Spotlight examines the issues that are driving organizations to replace older archive and backup-and-restore systems with business continuity and always-available solutions that can scale to handle extreme data growth while leveraging a cloudbased pricing model. The report also looks at the role of Storiant and its long-term storage services solution in the strategically important long-term storage market.
Tags : storiant, big data, analytics implementations, cloudbased pricing model, long-term storage services solution, long-term storage market
     Storiant
By: snowflake     Published Date: Jun 09, 2016
Today’s data, and how that data is used, have changed dramatically in the past few years. Data now comes from everywhere—not just enterprise applications, but also websites, log files, social media, sensors, web services, and more. Organizations want to make that data available to all of their analysts as quickly as possible, not limit access to only a few highly-skilled data scientists. However, these efforts are quickly frustrated by the limitations of current data warehouse technologies. These systems simply were not built to handle the diversity of today’s data and analytics. They are based on decades-old architectures designed for a different world, a world where data was limited, users of data were few, and all processing was done in on-premises datacenters.
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     snowflake
By: Revolution Analytics     Published Date: May 09, 2014
As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. Through techniques of supervised and unsupervised statistical learning, organizations can make important predictions and discover previously unknown knowledge to provide actionable business intelligence. In this guide, we’ll examine the principles underlying machine learning based on the R statistical environment. We’ll explore machine learning with R from the open source R perspective as well as the more robust commercial perspective using Revolution Analytics Enterprise (RRE) for big data deployments.
Tags : revolution analytics, data science, big data, machine learning
     Revolution Analytics
By: Adaptive Computing     Published Date: Feb 27, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: Commvault ABM Oct     Published Date: Jul 17, 2019
Enterprises are cobbling together all the pieces that make up a digital business - improved analytics, scalable architecture, automation, and more engaging customer experiences, just to name a few. At the same time, they're facing the ever-present threats of cyber attacks and data breaches.
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     Commvault ABM Oct
By: Zaloni     Published Date: Apr 24, 2019
Why your data catalog won’t deliver significant ROI According to Gartner, organizations that provide access to a curated catalog of internal and external data assets will derive twice as much business value from their analytics investments by 2020 than those that do not. That’s a ringing endorsement of data catalogs, and a growing number of enterprises seem to agree. In fact, the global data catalog market is expected to grow from US$210.0 million in 2017 to US$620.0 million by 2022, at a Compound Annual Growth Rate (CAGR) of 24.2%. Why such large and intensifying demand for data catalogs? The primary driver is that many organizations are working to modernize their data platforms with data lakes, cloud-based data warehouses, advanced analytics and various SaaS applications in order to grow profitable digital initiatives. To support these digital initiatives and other business imperatives, organizations need more reliable, faster access to their data. However, modernizing data plat
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     Zaloni
By: Hewlett Packard Enterprise     Published Date: May 10, 2019
The performance of enterprise applications will have a direct impact on business activities and outcomes. The quality of the delivery of applications will depend on how smoothly the underlying data infrastructure operates. ? Optimal application performance and delivery is difficult to achieve in complex environments. ? Many IT infrastructure and operations teams are stretched to the breaking point. ? Predictive analytics and machine learning can be applied to great effect
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     Hewlett Packard Enterprise
By: HPE Intel     Published Date: Mar 15, 2016
As more enterprises adopt technologies such as cloud, mobile, and analytics to help achieve strategic competitive advantage, CIOs and IT managers must support business-critical processes at a very high level across the enterprise. At the same time, IT organizations must manage complex hybrid IT infrastructures that include both cloud and on-premises technologies from multiple vendors and support providers. IDC believes that to tackle these challenges, IT organizations should look to support providers for comprehensive offerings to help optimize IT operations and improve the efficiency of IT service delivery. In addition, IDC recommends that IT organizations looking to manage rapid change in today’s IT landscape consider support providers with a record of innovative support services and a focus on advanced technology in support delivery.
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     HPE Intel
By: Hewlett Packard Enterprise     Published Date: Jul 19, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: Top 5 causes of downtime and poor performance across the infrastructure stack How machine learning and predictive analytics can prevent issues Steps you can take to boost performance and availability"
Tags : cloud, nimble storage, infrastructure
     Hewlett Packard Enterprise
By: Oracle     Published Date: Oct 20, 2017
What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i
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     Oracle
By: Pega     Published Date: May 25, 2016
Customer insights professionals face the challenging task of delivering contextually relevant experiences across the customer life cycle. They need to work with their business technology counterparts to integrate enterprise marketing technologies that manage customer data, provide real-time analytics and insights, and automate cross-channel interactions. Here is where Real-Time Interaction Management (RTIM) is critical, according to The Forrester Wave™: Real-Time Interaction Management, Q3 2015 report, which identified the 11 most significant technology providers in this space across 35 criteria. Forrester defines RTIM as “Enterprise marketing technology that delivers contextually relevant experiences, value, and utility at the appropriate moment in the customer life cycle via preferred customer touchpoints,” and identifies Pegasystems as one a leader in this very diversified pack. Download this Forrester Wave report to
Tags : interaction management, business technology, enterprise, forrester, best practices, pegasystems
     Pega
By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: -Top 5 causes of downtime and poor performance across the infrastructure stack -How machine learning and predictive analytics can prevent issues -Steps you can take to boost performance and availability
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     Hewlett Packard Enterprise
By: Oracle CX     Published Date: Oct 20, 2017
Oracle’s new cloud platform, included a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in memory and can prevent hacking explo
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     Oracle CX
By: Oracle CX     Published Date: Oct 20, 2017
On Thursday June 30th, we announced Oracle’s new cloud platform, including a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in
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     Oracle CX
By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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     Oracle CX
By: Gigamon     Published Date: Oct 19, 2017
Register for the Enterprise Strategy Group’s Research Insights Paper, Understanding the State of Network Security Today to learn more about the challenges, changes, best practices and solution requirements for network security operations and tools. See why ESG recommends improving network visibility and reducing security vulnerabilities by consolidating tools through a platform-based approach to visibility in which data, analytics and reports from multiple tools are aggregated and consumed in one control panel. Download to learn more.
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     Gigamon
By: Gigamon     Published Date: Oct 19, 2017
Read the Joint Solution Brief Gigamon Improves Security Visibility with Splunk Enterprise to see how to effectively analyze network events for security threats. Benefits include enhanced visibility and deeper, faster security analytics and intelligence based on all machine data (not just security events), among many others. Download now!
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     Gigamon
By: Gigamon     Published Date: Oct 25, 2017
Read the Joint Solution Brief Accelerate Threat Detection and Response to learn how Gigamon helps Splunk Enterprise users effectively analyze and remediate network security threats. Benefits include enhanced visibility and deeper, faster security analytics from precise, targeted network metadata generated from the traffic flowing in your network. Also learn how automation of common security tasks, across the Gigamon platform and third-party security tools, from within the Splunk platform helps increase analyst efficiency and reduce errors.
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     Gigamon
By: Riverbed     Published Date: Jan 25, 2018
This Enterprise Management Associates® (EMA™) research summary, sponsored by Riverbed®, highlights some of the key findings of EMA’s landmark report, “Network Management Megatrends 2016: Managing Networks in the Era of the Internet of Things, Hybrid Cloud, and Advanced Network Analytics.” It examines several major areas of change and evolution affecting network management. These “megatrends” include hybrid cloud networking, the Internet of Things (IoT), advanced network analytics, network management outsourcing, and network management tool consolidation.
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     Riverbed
By: TIBCO Software GmbH     Published Date: Jan 15, 2019
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
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     TIBCO Software GmbH
By: SAP     Published Date: May 22, 2012
Is turning data into information still a challenge for your company? If so, you are not alone. View this on-demand Webinar with SAP and HP to learn how you can manage ever-increasing amounts of data; provide this data to business users to make critical decisions in a timely fashion; and enable true self-service business intelligence (BI) for business users.
Tags : sap, business solutions, business technology, enterprise, technology, enterprise analytics
     SAP
By: Akamai Technologies     Published Date: Sep 11, 2017
Malicious botnets present multiple challenges to enterprises — some threaten security, and others merely impact performance or web analytics. A growing concern in the bot environment is the practice of credential stuffing, which capitalizes on both a bot’s ability to automate repeat attempts and the growing number of online accounts held by a single user. As bot technologies have evolved, so have their methods of evading detection. This report explains how the credential stuffing exploit challenges typical bot management strategies, and calls for a more comprehensive approach.
Tags : web analytics, frost & sullivan, bot management, botnet
     Akamai Technologies
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