analytics organizations

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By: IBM     Published Date: Jun 05, 2014
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
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     IBM
By: IBM     Published Date: Sep 16, 2015
6 criteria for evaluating a high-performance cloud services providers Engineering, scientific, analytics, big data and research workloads place extraordinary demands on technical and high-performance computing (HPC) infrastructure. Supporting these workloads can be especially challenging for organizations that have unpredictable spikes in resource demand, or need access to additional compute or storage resources for a project or to support a growing business. Software Defined Infrastructure (SDI) enables organizations to deliver HPC services in the most efficient way possible, optimizing resource utilization to accelerate time to results and reduce costs. SDI is the foundation for a fully integrated environment, optimizing compute, storage and networking infrastructure to quickly adapt to changing business requirements, and dynamically managing workloads and data, transforming a s
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     IBM
By: IBM     Published Date: May 20, 2015
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
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     IBM
By: Data Direct Networks     Published Date: Dec 31, 2015
Parallelism and direct memory access enable faster and more accurate SAS analytics using Remote Direct Memory Access based analytics and fast, scalable,external disk systems with massively parallel access to data, SAS analytics driven organizations can deliver timely and accurate execution for data intensive workfl ows such as risk management, while incorporating larger datasets than using traditional NAS.
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     Data Direct Networks
By: CA Technologies EMEA     Published Date: Sep 11, 2018
Software drives competitive advantage more than ever at an increasing velocity for releases along with higher, overwhelming levels of deployment complexity. Dramatic growth in mobile applications, analytics, systems of engagement, and cloud demands that organizations respond adaptively, even as resource constraints make it challenging to nearly impossible to do so. As a result of these combined factors, IDC sees increased interest in, demand for, and adoption of agile approaches to development and also for business initiatives driving adoption of agile approaches to overall project, program, and portfolio management. As we receive inquiry on this area increasingly, it makes sense to assess this market.
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     CA Technologies EMEA
By: TIBCO Software APAC     Published Date: Aug 13, 2018
Whilst businesses of all kinds are utilizing data analytics, many are still only using it to make simple changes that lead to a set of rigid processes. Whereas the more customer-focused organizations are realizing that to deliver exceptional experiences, they need to be able to react to customer data in real-time and predict what might happen next. And that means going beyond simple analytics. Read our whitepaper to discover what analyst firm Forrester has identified as the Enterprise Insight Platform, technology designed to enable companies to transform into truly data-driven businesses.
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     TIBCO Software APAC
By: TIBCO Software APAC     Published Date: Aug 15, 2018
Expanding analytic capabilities are critical to digitizing the business, optimizing costs, accelerating innovation, and surviving digital disruption Historically, manufacturers were almost solely focused on reducing costs by applying automation and analytics to engineering, R&D, manufacturing operations, and quality organizations. Even though the strategies used within these areas are still needed, they are not sufficient to ensure business survival and continuity in the age of Industry 4.0 and the IoT. Today, it is paramount that smart manufacturers broaden their scope because disruptive innovations in data acquisition, storage, and analytics technology have enabled an entirely new degree of automation and virtualization, promising a complete 360-degree high-fidelity virtual data-driven integrated views of all operations—from suppliers and supply chains, through equipment, processes, and manufacturing practices, to final product testing and customer satisfaction. Download this paper
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     TIBCO Software APAC
By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
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     Amazon Web Services
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.
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     NetApp
By: Sitecore     Published Date: Nov 04, 2009
This report highlights the strategic value of a next generation web content management system integrated with lead scoring, email marketing, customer relationship management, and web analytics. The report links the technology and practices of Best-in-Class organizations to engage customers, provide personalized experiences and manage the lead lifecycle.
Tags : sitecore, aberdeen, lifecycle management, web content management, analytics, crm, emarketing, email marketing, lead generation
     Sitecore
By: Mintigo     Published Date: Sep 05, 2018
One of the most common use cases for AI in B2B is to make predictions about which accounts are most likely to buy and which leads are most likely to convert. However, use cases for AI are being extended beyond predictive account and lead scoring to include decision-making and process automation as well. Download this SiriusDecisions technology perspective on Predictive Analytics and Artificial Intelligence Technology to learn more. This paper will cover: • The benefits, evolution and capabilities of AI technology solutions for B2B organizations • The core and extended capability groups of AI • The business priorities supported by AI Fill out the form to get your free copy!
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     Mintigo
By: SAP     Published Date: Feb 03, 2017
To better understand the benefits, costs, and risks associated with implementation of SAP Business Objects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to provide the conclusions of this cost and benefit analysis.
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     SAP
By: SAP     Published Date: Feb 03, 2017
To better understand the benefits, costs, and risks associated with implementation of SAP BusinessObjects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to report cost and benefit findings
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     SAP
By: Hewlett Packard Enterprise     Published Date: May 11, 2018
If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem. Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.
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     Hewlett Packard Enterprise
By: SAP     Published Date: May 18, 2014
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, it management
     SAP
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: 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
By: SAS     Published Date: Jan 17, 2018
For many of us, the term “smart city” conjures up images of sensors collecting data about everything from traffic patterns to energy use. It’s common for government leaders to think, “That’s not for us. We’re not there yet.” But if your organization is collecting data of any kind, you are in a position to use that data to create a smarter city for your citizens. Download this whitepaper for 10 examples of analytics being used to solve problems or simplify tasks for government organizations.
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     SAS
By: SAS     Published Date: Jan 17, 2018
This RSR custom research report explores the impact of omnichannel methods on merchandising, marketing and the supply chain; specifically, what analytical capabilities address the challenges that omnichannel selling and fulfillment pose for retailers. Consumers today routinely begin their shopping journeys online, but complete their purchases in nearby stores, in their “home” stores or delivered directly to their doors. Retail analytics enables organizations to capture data from their customers' journeys. Retailers that successfully deliver relevant omnichannel experiences while gaining a more sophisticated understanding of demand (where and how it is initiated) will enhance their brands’ value and create compelling and profitable customer relationships.
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     SAS
By: SAS     Published Date: Jan 17, 2018
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally. Learn more about key findings, including: Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics. Return on investment for analytics stems from the governing and sharing of data throughout the organization. Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.
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     SAS
By: SAS     Published Date: Jan 17, 2018
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
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     SAS
By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
Tags : pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking, it management, data management
     Pentaho
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: 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
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