big data

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Published By: Oracle     Published Date: Jan 08, 2018
In the age of the customer, businesses realize the need to take their big data insights further than they have before, in order to win, serve, and retain their customers. Today’s modern company has more data than ever before and is now looking to derive insights from the data that will help propel it forward. As firms move data analytics to the cloud, there is a new set of challenges and barriers to overcome, but with the help of insights-platforms-as-a-service, companies will be able to innovate with data and drive business forward.
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Oracle
Published By: Pure Storage     Published Date: Jan 12, 2018
Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions. Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.
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reporting, artificial intelligence, insights, organization, institution, recognition
    
Pure Storage
Published By: Pure Storage     Published Date: Jan 12, 2018
Everybody’s talking about big data. Huge promises have been made about its role in driving enterprises forward. But few organizations are realizing its true benefits. For those able to put data to good use, there’s much to be excited about. Data is transforming not only businesses, but entire industries, and the world as we know it. Today organizations are harnessing big data to do things like transform healthcare, provide eyesight for the visually impaired, and bringing us closer to autonomous cars
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automated intelligence, data, industry, autonomous, industrial, pure storage
    
Pure Storage
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Published By: IBM     Published Date: Oct 17, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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IBM
Published By: IBM     Published Date: Nov 08, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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ibm, cloud, cloud computing, database, ibm db2
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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db2. blu accelaration, big data, data analytics, disaster recovery
    
Group M_IBM Q1'18
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
The demand for databases is on the rise as organizations build next-generation business applications. NoSQL offers enterprise architecture (EA) pros new choices to store, process, and access new data formats, deliver extreme web-scale, and lower data management costs. Forrester’s 26-criteria evaluation of 15 big data NoSQL solutions will help EA pros understand the choices available and recommend the best for their organization. This report details our findings about how each vendor fulfills our criteria and where they stand in relation to each other to help EA.
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nosql, market, industries, strategy, presence, vendor
    
AstuteIT_ABM_EMEA
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
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Oracle
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
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical. These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most compani
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Security has become top of mind for CIOs, and CEOs. Encryption at rest is a piece of the solution, but not a big piece. Encryption over the network is another piece, but only a small piece. These and other pieces do not fit together well; they need to unencrypt and reencrypt the data when they move through the layers, leaving clear versions that create complex operational issues to monitor and detect intrusion. Larger-scale high-value applications requiring high security often use Oracle middleware, including Java and Oracle database. Traditional security models give the data to the processors to encrypt and unencrypt, often many times. The overhead is large, and as a result encryption is used sparingly on only a few applications. The risk to enterprises is that they may have created an illusion of security, which in reality is ripe for exploitation. The modern best-practice security model is an end-to-end encryption architecture. The application deploys application-led encryption s
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Oracle
Published By: MIT Academy of Engineering, Pune     Published Date: Mar 05, 2013
A Java application that will successfully be able to retrieve, insert & delete data from our database which will be implemented in HBase along with.Basically the idea is to provide much faster, safer method to transmit & receive huge amounts of data
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MIT Academy of Engineering, Pune
Published By: SAP     Published Date: Mar 09, 2017
There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.
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SAP
Published By: SAP     Published Date: Mar 09, 2017
Learn how CIOs can set up a system infrastructure for their business to get the best out of Big Data. Explore what the SAP HANA platform can do, how it integrates with Hadoop and related technologies, and the opportunities it offers to simplify your system landscape and significantly reduce cost of ownership.
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SAP
Published By: HPE APAC     Published Date: Jun 16, 2017
The bar has been raised higher than ever, and the role of IT is evolving to meet it. As a result, IT must support applications and services that make it possible for the business to provide new, diverse customer experiences while generating expanding revenues via the emergent crown jewels of business: big data, cloud, and mobility. Read on to find out more.
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HPE APAC
Published By: Cisco EMEA Tier 3 ABM     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
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big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
    
Cisco EMEA Tier 3 ABM
Published By: ExactTarget     Published Date: Aug 14, 2014
Marketing as you know it will never be the same. There’s a fundamental shift in relationships between brands and customers—fueled by smartphones, social media, and today’s always-on, always-connected mentality. Marketers have access to more customer data (big data) than ever before. But the quantity of data only matters if you’re smart about using it—to power 1:1 customer journeys.
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marketing cloud, target, big data, brands, customers, social media, smartphones, always-on
    
ExactTarget
Published By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
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