it 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: IBM     Published Date: Sep 02, 2014
Advanced analytics strategies yield the greatest benefits in terms of improving patient and business outcomes when applied across the entire healthcare ecosystem. But the challenge of collaborating across organizational boundaries in order to share information and insights is daunting to many stakeholders. In this worldwide survey of 555 healthcare providers, payers and life sciences organizations, you will learn the importance of implementing collaborative analytics strategies that: Manage, integrate and interpret data generated at all stages of the healthcare value chain Achieve the right balance of skills in order to translate data into actionable insights Focus on executive sponsorship and enterprise-wide adoption with metrics to measure and track success Position yourself to harness data, create and share insights, make informed decisions, and improve the performance of the entire healthcare ecosystem in which you operate.
Tags : ibm, analytics acrosss ecosystem
     IBM
By: IBM     Published Date: Sep 02, 2014
In today’s stringent financial services regulatory environment with exponential growth of data and dynamic business requirements, Risk Analytics has become integral to businesses. IBM Algorithmics provides very sophisticated analyses for a wide range of economic scenarios that better quantify risk for multiple departments within a firm, or across the enterprise. With Algorithmics, firms have a better handle on their financial exposure and credit risks before they finalize real-time transactions. But this requires the performance and agility of a scalable infrastructure; driving up IT risk and complexity. The IBM Application Ready Solution for Algorithmics provides an agile, reliable and high-performance infrastructure to deliver trusted risk insights for sustained growth and profitability. This integrated offering with a validated reference architecture delivers the right risk insights at the right time while lowering the total cost of ownership.
Tags : ibm, it risk, financial risk analytics
     IBM
By: IBM     Published Date: May 20, 2015
IBM Platform Symphony - accelerate big data analytics – This demonstration will highlight the benefits and features of IBM Platform Symphony to accelerate big data analytics by maximizing distributed system performance, fully utilizing computing resources and effectively harnessing the power of Hadoop.
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     IBM
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: IBM     Published Date: May 20, 2015
There is a lot of hype around the potential of big data and organizations are hoping to achieve new innovations in products and services with big data and analytics driving more concrete insights about their customers and their own business operations. To meet these challenges, IBM has introduced IBM® Spectrum Scale™. The new IBM Spectrum Scale storage platform has grown from GPFS, which entered the market in 1998. Clearly, IBM has put significant development into developing this mature platform. Spectrum Scale addresses the key requirements of big data storage - extreme scalability for growth, reduced overhead of data movement, easy accessibility , geographic location independence and advanced storage functionality. Read the paper to learn more!
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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: Sep 16, 2015
The impact of the 2008 financial crisis affects not only Sell Side firms - the focus of discussions - but Buy Side and Insurance firms. Dodd Frank Act targets all systemically important firms. This study conducted in partnership with Waters Technology, an Incisive Media publication, focuses these firms. The report finds that they are facing intense pressure on multiple fronts including stricter liquidity and solvency risk regulations, and changing market conditions. Like Sell Side firms, they require more innovative business models and analytics to meet these challenges and to deliver growth and performance.
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     IBM
By: TIBCO     Published Date: Nov 09, 2015
As one of the most exciting and widely adopted open-source projects, Apache Spark in-memory clusters are driving new opportunities for application development as well as increased intake of IT infrastructure. Apache Spark is now the most active Apache project, with more than 600 contributions being made in the last 12 months by more than 200 organizations. A new survey conducted by Databricks—of 1,417 IT professionals working with Apache Spark finds that high-performance analytics applications that can work with big data are driving a large proportion of that demand. Apache Spark is now being used to aggregate multiple types of data in-memory versus only pulling data from Hadoop. For solution providers, the Apache Spark technology stack is a significant player because it’s one of the core technologies used to modernize data warehouses, a huge segment of the IT industry that accounts for multiple billions in revenue. Spark holds much promise for the future—with data lakes—a storage repo
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     TIBCO
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: RYFT     Published Date: Apr 03, 2015
The new Ryft ONE platform is a scalable 1U device that addresses a major need in the fast-growing market for advanced analytics — avoiding I/O bottlenecks that can seriously impede analytics performance on today's hyperscale cluster systems. The Ryft ONE platform is designed for easy integration into existing cluster and other server environments, where it functions as a dedicated, high-performance analytics engine. IDC believes that the new Ryft ONE platform is well positioned to exploit the rapid growth we predict for the high-performance data analysis market.
Tags : ryft, ryft one platform, 1u deivce, advanced analytics, avoiding i/o bottlenecks, idc
     RYFT
By: Impetus     Published Date: Feb 04, 2016
This white paper explores strategies to leverage the steady flow of new, advanced real-time streaming data analytics (RTSA) application development technologies. It defines a thoughtful approach to capitalize on the window of opportunity to benefit from the power of real-time decision making now, and still be able to move to new and emerging technologies as they become enterprise ready.
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     Impetus
By: Impetus     Published Date: Mar 15, 2016
Streaming analytics platforms provide businesses a method for extracting strategic value from data-in-motion in a manner similar to how traditional analytics tools operate on data-at rest. Instead of historical analysis, the goal with streaming analytics is to enable near real-time decision making by letting companies inspect, correlate and analyze data even as it flows into applications and databases from numerous different sources. Streaming analytics allows companies to do event processing against massive volumes of data streaming into the enterprise at high velocity.
Tags : impetus, guide to stream analytics, real time streaming analytics, streaming analytics, real time analytics, big data analytics
     Impetus
By: TIBCO     Published Date: Sep 02, 2014
In this Guide you will learn how predictive analytics helps your organization predict with confidence what will happen next so that you can make smarter decisions and improve business outcomes. It is important to adopt a predictive analytics solution that meets the specific needs of different users and skill sets from beginners, to experienced analysts, to data scientists.
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     TIBCO
By: IBM     Published Date: Nov 14, 2014
Join Gartner, Inc. and IBM Platform Computing for an informative webinar where you will learn how to combine best of breed analytic solutions to provide a low latency, shared big data infrastructure. This helps government IT departments make faster decisions by analyzing massive amounts of data, improving security, detecting fraud, enabling faster decisions and saving cost by optimizing and sharing your existing infrastructure.
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     IBM
By: IBM     Published Date: Feb 13, 2015
In the age of "big data," it's essential for any organization to know how to analyze and manage their ever increasing stores of information. Packed with everything you need to know about Hadoop analytics, this handy guide provides you with a solid understanding of the critical big data concepts and trends, and suggests ways for you to revolutionize your business operations through the implementation of cost-effective, high performance Hadoop technology.
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     IBM
By: Kx Systems     Published Date: Jan 16, 2015
?Kdb+ is a column-based relational database with extensive in-memory capabilities, developed and marketed by Kx Systems. Like all such products, it is especially powerful when it comes to supporting queries and analytics. However, unlike other products in this domain, kdb+ is particularly good (both in terms of performance and functionality) at processing, manipulating and analysing data (especially numeric data) in real-time, alongside the analysis of historical data. Moreover, it has extensive capabilities for supporting timeseries data. For these reasons Kx Systems has historically targeted the financial industry for trading analytics and black box trading based on real-time and historic data, as well as realtime risk assessment; applications which are particularly demanding in their performance requirements. The company has had significant success in this market with over a hundred major financial institutions and hedge funds deploying its technology. In this paper, however, we wa
Tags : kx systems, kdb+, relational database
     Kx Systems
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: Group M_IBM Q3'19     Published Date: Jun 24, 2019
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
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     Group M_IBM Q3'19
By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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     Infinidat EMEA
By: Infinidat EMEA     Published Date: Jun 10, 2019
Digital disruption, economic instability, political upheavals and skills shortages have all at some point in the past 24 months been blamed for business failure, or at the very least, lost profitability and earnings. It’s perhaps not a huge surprise that a Gartner CEO survey on business priorities revealed that digital business is a top priority for next year. Survey respondents were asked whether they have a management initiative or transformation program to make their business more digital. The majority (62 percent) said they did. Of those organisations, 54 percent said that their digital business objective is transformational while 46 percent said the objective of the initiative is optimisation.* So, for businesses it’s a case of learning to evolve and be agile, to use technology to help compete more efficiently and not fall victim to inertia. As businesses become increasingly dependent on the insights from data analytics and face-up to competition fuelled by the 24/7 society of in
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     Infinidat EMEA
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: Workday France     Published Date: Jul 05, 2019
Whether informing talent strategy or building more effective teams, data-driven insights about your workforce can set you up for success. This eBook from Human Capital Institute explores how people analytics can empower your entire organisation. Read now."
Tags : workforce-technologie, digitale strategie
     Workday France
By: Adobe     Published Date: Jun 26, 2019
Artificial intelligence (AI) and analytics make a good team. With AI-powered analytics, you and your team can concentrate on the initiatives that really matter instead of burying yourself in reports.
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     Adobe
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