big data solution

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Published By: IBM     Published Date: Jan 14, 2015
Cloud-delivered big data analytics presents an enormous opportunity for organizations that want to become more agile, more efficient and more competitive. To capitalize on the full potential of this opportunity, businesses need cloud-enabled big data analysis solutions that are flexible, simple, secure and open.
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big data, data management, the cloud, cloud solutions, data, data analytics, client engagement, computing model, scale on demand, data center
    
IBM
Published By: Dell EMC     Published Date: Oct 08, 2015
Download this white paper to learn how the company deployed a Dell and Hadoop cluster based on Dell and Intel® technologies to support a new big data insight solution that gives clients a unified view of customer data.
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Dell EMC
Published By: Pure Storage     Published Date: Dec 05, 2018
Data is the new currency. Is your organization capitalizing on the full potential of data analytics? In this big data primer, you will learn about the 3 key challenges facing organizations today: managing overwhelming amounts of data, leveraging new complex tools/technologies, and developing the necessary skills and infrastructure. And since storage is where your organization's data lives, it’s a pivotal part of the infrastructure jigsaw puzzle. Thus with a “tuned for everything” storage solution that is purpose-built for modern analytics, you can confidently harness the power of your data to drive your enterprise forward.
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Pure Storage
Published By: IBM     Published Date: Mar 29, 2017
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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cloud, analytics, data, organization, ibm
    
IBM
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
One of the biggest changes faces organizations making purchasing and deployment decisions about analytic databases -- including relational data warehouses -- is whether to opt for a cloud solution.
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Group M_IBM Q2'19
Published By: IBM     Published Date: May 19, 2015
Predictive analytics is within easy reach for all enterprises if they choose the right big data predictive analytics solution to meet their needs.
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predictive analytics, predictive analytics solutions, big data, enterprise. advanced analytics, application development
    
IBM
Published By: IBM     Published Date: Sep 27, 2013
Analytics: The Real-World Use of Big Data - How innovative enterprises in the midmarket extract value from uncertain data This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
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ibm, big data, big data solutions, midmarket businesses, analytics, it management, data management, business technology
    
IBM
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, data center
    
IBM
Published By: SevOne     Published Date: Jul 07, 2015
Because inventory is usually one of the biggest numbers on their balance sheet, effective inventory control and management is a vital function to help insure the continued success of distribution and manufacturing and companies.
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erp, inventory management, big data, manufacturing, distribution, business technology
    
SevOne
Published By: Sage     Published Date: Jul 08, 2015
Download this white paper to learn more about how to improve your organization's inventory management and control.
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inventory management, big data, inventory control, cost containment, customer service
    
Sage
Published By: IBM     Published Date: May 07, 2013
This book brings a practitioner’s view to Big Data Analytics. Download this ebook to read a practical viewpoint into leveraging analytics for Big Data. This book also draws material from a large number of workshops and interviews with business and IT leaders. Learn more about ‘Big Data and Business Analytics’ through IBM’s latest market leading solutions. Register and attend this complimentary virtual event on June 11 by IBM Business Analytics
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practical viewpoint, analytics, big data, interviews, business
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data. To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
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data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
    
IBM
Published By: Cisco     Published Date: May 15, 2015
Whitepaper focused on how leaning on bundled solutions and proven expertise can achieve big data success.
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big data, strategy, cisco, internet
    
Cisco
Published By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance, knowledge management, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance, knowledge management, data management, data center
    
IBM
Published By: IBM     Published Date: Jul 14, 2015
This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, data warehouse, data center, information governance, analytics, big data analytics, business management, data management
    
IBM
Published By: IBM     Published Date: Apr 06, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, analytics, unstructured content, enterprise information, ibm, it management, knowledge management, storage, data management
    
IBM
Published By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, ibm, big data outcomes, information governance, big data analytics, it management, data management, data center
    
IBM
Published By: IBM     Published Date: Apr 05, 2016
IBM SPSS Solutions offer a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end.
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ibm, big data, little data, ibm spss solutions, knowledge management, data management, business technology
    
IBM
Published By: IBM APAC     Published Date: Aug 25, 2017
Transitioning from traditional IT to cloud IT is not an all-at-once, big bang effort. Rather, the cloud adoption process should be an agile, incremental process. And the first part of that process is understanding the different cloud models. Contrary to popular belief, cloud isn’t necessarily only public cloud, multi-tenant, and hosted in a vendor’s data center. It can also be private cloud, single-tenant, and/or hosted in a corporate data center. Often the best solution is a hybrid combination of these options. This paper will show you the advantages of hybrid cloud applications and explore the considerations you should make to find an optimal solution for your organization.
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cost reduction, cost optimization, business agility, innovation, business models
    
IBM APAC
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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Amazon Web Services
Published By: IBM     Published Date: May 07, 2013
Read this whitepaper to learn how businesses take advantage of the power of the cloud to build strong analytically oriented teams, adopt new ways to use information and jump ahead of their competition. Learn more about ‘Big Data and Business Analytics’ through IBM’s latest market leading solutions. Register and attend this complimentary virtual event on June 11 by IBM Business Analytics
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analytics, cloud, business, innovation, computing, information, advantage, power
    
IBM
Published By: Fujitsu     Published Date: Dec 22, 2015
This whitepaper reveals how Ceph can be summed up as an open source software solution conceived and built to deliver hyper-scale performance and almost limitless expandability.
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ceph, storage, software, big data, data, scalability, storage infrastructure, software solution, architecture, software defined storage
    
Fujitsu
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