big data analytic applications

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Overcoming Petabyte-Scale Storage Challenges for Big Data and Analytics

Published 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

The Business Value of Cisco UCS for Big Data and Analytics

Published By: Cisco EMEA     Published Date: Nov 08, 2018
Digital transformation (DX) — a technology-driven business strategy — enables firms to gain or expand their competitive differentiation by embracing data-driven decision-making processes, whether for increasing operational efficiencies, developing new products and services, increasing customer satisfaction and retention, or getting a better intelligence on the market. Big Data and analytics (BDA) applications form the foundation for enterprisewide digital transformation initiatives. To find out more download this whitepaper today.
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Cisco EMEA

Oracle SPARC T8 and SPARC M8 Architecture

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

Software in Silicon: Enabling Secure Infrastructures for the Real-Time Enterprise

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

FlashBlade Data Sheet

Published By: Pure Storage     Published Date: Nov 02, 2017
In the new age of big data, applications are leveraging large farms of powerful servers and extremely fast networks to access petabytes of data served for everything from data analytics to scientific discovery to movie rendering. These new applications demand fast and efficient storage, which legacy solutions are no longer capable of providing.
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big data analytics, genomics, medicine, digital science, engineering, design, software, development, next-generation
    
Pure Storage

Hyperconverged infrastructure: Preparing Asia’s businesses for the future

Published By: Lenovo - APAC     Published Date: Jan 28, 2019
Asian ICT infrastructure investment is exploding as businesses review and modernise their data-centre architectures to keep up with the service demands of a growing and increasingly sophisticated population. Demand for cloud services, particularly to support big-data analytics initiatives, is driving this trend. Frost & Sullivan, for example, believes the Asia-Pacific cloud computing market will grow at 28.4 percent annually through 2022. Despite this growth, many businesses are also rapidly realising that public cloud is not the best solution for every need as theydo not always offer the same level of visibility, performance, and control as on-premises infrastructure.This reality is pushing many companies towards the middle ground of hybrid IT, in which applications and infrastructure are distributed across public cloud and self-managed data centre infrastructure. Read about Medical company Mutoh and how it took advantage of the latest technology.
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lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC

Hyperconverged infrastructure: Preparing Asia’s businesses for the future

Published By: Lenovo - APAC     Published Date: Feb 11, 2019
Asian ICT infrastructure investment is exploding as businesses review and modernise their data-centre architectures to keep up with the service demands of a growing and increasingly sophisticated population. Demand for cloud services, particularly to support big-data analytics initiatives, is driving this trend. Frost & Sullivan, for example, believes the Asia-Pacific cloud computing market will grow at 28.4 percent annually through 2022. Despite this growth, many businesses are also rapidly realising that public cloud is not the best solution for every need as theydo not always offer the same level of visibility, performance, and control as on-premises infrastructure.This reality is pushing many companies towards the middle ground of hybrid IT, in which applications and infrastructure are distributed across public cloud and self-managed data centre infrastructure. Read about Medical company Mutoh and how it took advantage of the latest technology.
Tags : 
lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC

A Discussion With Pure Storage’s Brian Gold on Big Data Analytics for Apache Spark

Published By: Pure Storage     Published Date: Oct 09, 2018
Apache® Spark™ has become a vital technology for development teams looking to leverage an ultrafast in-memory data engine for big data analytics. Spark is a flexible open-source platform, letting developers write applications in Java, Scala, Python or R. With Spark, development teams can accelerate analytics applications by orders of magnitude
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Pure Storage

Consistent, Reusable Analytics for Big Data: The Hallmark of Analytic Applications

Published By: Teradata     Published Date: Jul 15, 2015
This paper examines the value of big data applications as a means to ensure pervasive availability of big data analytics in the organization.
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analytics, big data, applications, lob, application integration, application performance management
    
Teradata

A New Breed of Servers for Digital Transformation

Published By: IBM     Published Date: Jul 02, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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IBM

Reinventing Business Analytics

Published By: Visier     Published Date: Jan 25, 2019
John Schwarz founded Visier to address what he saw as the major failing of business intelligence and big data analytics. He had a front row seat in this market while leading Business Objects, the largest global business intelligence provider (acquired by SAP). John and co-founder Ryan Wong’s vision was to completely reinvent the approach to analytics, providing instant and complete, domain-specific applications to business leaders, answering their important strategic questions and leading them to adopt best management practices. Their applied business analytics project is working. Today, more than a hundred blue chip companies have selected Visier as their people strategy platform and are achieving incredible results. And that’s just the beginning.
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Visier

Oracle SPARC T8 and SPARC M8 Architecture

Published By: Oracle     Published Date: Oct 20, 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 bette
Tags : 
    
Oracle

Software in Silicon: Enabling Secure Infrastructures for the Real-Time Enterprise

Published By: Oracle     Published Date: Oct 20, 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 bette
Tags : 
    
Oracle

Getting Started with Amazon Redshift – Best Practices

Published 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

Optimizing Amazon Redshift, A Real-World Guide

Published 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

Ovum SWOT Assessment: HP Service Anywhere

Published By: HP Software     Published Date: Oct 20, 2015
The HP Service Anywhere user interface is currently one of the best offered by an ITSM solution.
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swot, big data, analytics, management, applications, application integration, best practices, business intelligence
    
HP Software

Architecting a Big Data Platform for Analytics by Mike Ferguson

Published By: IBM     Published Date: May 02, 2014
These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse.
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ibm, big data platform, architecting big data, analytics, intelligent business strategies, data complexity, data types, workload growth, workload complexity, big data analytic applications, operational decisions, multi-structured data, querying data, scalable data management, analytical ecosystem, hadoop solutions, it management, data management, best practices, business intelligence
    
IBM

A New Breed of Servers for Digital Transformation

Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
Tags : 
    
Group M_IBM Q418

Cloud For Dummies E-Book

Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Organizations are faced with providing secure authentication, authorization, and Single Sign On (SSO) access to thousands of users accessing hundreds of disparate applications. Ensuring that each user has only the necessary and authorized permissions, managing the user’s identity throughout its life cycle, and maintaining regulatory compliance and auditing further adds to the complexity. These daunting challenges are solved by Identity and Access Management (IAM) software. Traditional IAM supports on-premises applications, but its ability to support Software-as-a-Service (SaaS)-based applications, mobile computing, and new technologies such as Big Data, analytics, and the Internet of Things (IoT) is limited. Supporting on-premises IAM is expensive, complex, and time-consuming, and frequently incurs security gaps. Identity as a Service (IDaaS) is an SaaS-based IAM solution deployed from the cloud. By providing seamless SSO integration to legacy on-premises applications and modern cloud-
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Group M_IBM Q418

Optimizing Amazon Redshift, A Real-World Guide

Published By: AWS     Published Date: Sep 04, 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 technology
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AWS

A Practical Guide to Transform Manufacturing Operations with Smart Pull

Published By: Dassault Systèmes     Published Date: Jun 19, 2018
This white paper outlines a framework that emphasizes digitization and business transformation and the new opportunities pull processes bring. The mechanism of “Pull” processes—those triggered by an actual event instead of a forecast—is nothing new. It is at the heart of many successful manufacturing strategies. Recent technological advances in digitization, including the harnessing of Big Data analytics, the use of the cloud, Business Process Management (BPM), social media, IIoT, and mobility, have extended the power of Pull beyond Lean manufacturing. In the wake of the current technological innovation wave, it is not uncommon for manufacturers to not know what next step to take. In light of these new developments, this white paper will focus on the mechanism of business transformation enabled by these technologies, which can be attributed to two major forces: the power of Pull and digitization. Nine practical applications are detailed, showing how innovative manufacturers can better
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Dassault Systèmes

A Discussion With Pure Storage’s Brian Gold on Big Data Analytics for Apache Spark

Published By: Pure Storage     Published Date: Jul 03, 2019
Apache® Spark™ has become a vital technology for development teams looking to leverage an ultrafast in-memory data engine for big data analytics. Spark is a flexible open-source platform, letting developers write applications in Java, Scala, Python or R. With Spark, development teams can accelerate analytics applications by orders of magnitude.
Tags : 
    
Pure Storage

Hyperconverged infrastructure: Preparing Asia’s businesses for the future

Published By: Lenovo - APAC     Published Date: Jan 28, 2019
Asian ICT infrastructure investment is exploding as businesses review and modernise their data-centre architectures to keep up with the service demands of a growing and increasingly sophisticated population. Demand for cloud services, particularly to support big-data analytics initiatives, is driving this trend. Frost & Sullivan, for example, believes the Asia-Pacific cloud computing market will grow at 28.4 percent annually through 2022. Despite this growth, many businesses are also rapidly realising that public cloud is not the best solution for every need as they do not always offer the same level of visibility, performance, and control as on-premises infrastructure.This reality is pushing many companies towards the middle ground of hybrid IT, in which applications and infrastructure are distributed across public cloud and self-managed data centre infrastructure. Read about Medical company Mutoh and how it took advantage of the latest technology.
Tags : 
lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC
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