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By: Cox Business     Published Date: Dec 19, 2016
As we continue to move forward into an age of big data, optimization, and greater convenience through the capabilities of better networking technologies, opportunities have never been greater to use technology to make for a truly seamless hospitality experience. However, growing dependence on your network for everything from booking to entertainment can also mean that hospitality networks hold greater amounts of data than ever before. This makes them a tempting target for hackers.
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     Cox Business
By: Cox Business     Published Date: Dec 19, 2016
As the healthcare industry continues to move forward into an age of big data, optimization, and greater coordination of care through the capabilities of better networking technologies, opportunities have never been greater to use technology to truly improve how healthcare professionals interacts with patients. However, growing dependence on your network for everything from medical records to billing information can also mean that healthcare networks hold greater amounts of data than ever before. This makes them a tempting target for hackers.
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     Cox Business
By: Dun & Bradstreet     Published Date: Mar 03, 2017
Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments. By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models. View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.
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     Dun & Bradstreet
By: HP Enterprise Business     Published Date: Jan 20, 2017
Six keys to reducing cost with a fast, agile, and efficient big data service desk. Download now to learn more!
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     HP Enterprise Business
By: IBM     Published Date: Jan 27, 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.
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     IBM
By: IBM     Published Date: Jan 27, 2017
The bottom line is that those that have the most customer insight will win because they know what customers want. So the question is how will you get that insight? What is it that you don’t know about customers in the market(s) that you operate in? Do you have all the attributes about customers in your MDM system that could be of value to your business? Do you know about all the relationships that your customers have in your MDM system? In most cases, the answer to the above questions is no which inevitably means one thing. You need more data
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     IBM
By: IBM     Published Date: Jan 27, 2017
A big data integration platform that is flexible and scalable is needed to keep up with today’s ever-increasing big data volume.
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     IBM
By: IBM     Published Date: Jan 27, 2017
A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamlessly integrate with diverse technologies, from data marts to Apache Hadoop systems. And it must automatically discover, protect and monitor sensitive information as part of big data applications.
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     IBM
By: IBM     Published Date: Jan 27, 2017
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
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     IBM
By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. 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.
Tags : ibm, analytics, ecm, data, big data, information governance
     IBM
By: IBM     Published Date: Jan 19, 2017
With organizations keeping larger and larger quantities of data the question will come up that given dropping storage costs, does uncontrolled data growth even matter? It does matter, and in this IBM publication featuring Gartner research you will learn about this ever growing problem and ways for information managers to address solutions.
Tags : ibm, analytics, data, ecm, big data, information governance
     IBM
By: IBM     Published Date: Jan 27, 2017
Analytics relies on BI, Big Data, and data discovery to provide reporting, trend what-if analysis. Analytics is transforming data into insight.
Tags : ibm, analytics, business intelligence, data
     IBM
By: Schneider Electric     Published Date: Feb 17, 2017
In this white paper, we will look into: • The changing face of the colocation buyer • Industry structure, including mergers and acquisitions • The Internet of Things and big data • Edge computing • Cloud computing and Internet Giants • The impact of data center infrastructure management (DCIM) • Data center design architectures
Tags : colocation, iot, internet of things, big data, edge computing, cloud computing, dcim, data center infrastructure management
     Schneider Electric
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
By: Lenovo     Published Date: Jan 19, 2017
Accessing, analyzing, and actioning with big data are among the key challenges facing every enterprise. In this detailed report from Forrester, you’ll see key drivers and challenges with Big Data, AND some clear recommendations on how to proceed. Get the white paper to see Forrester's key findings.
Tags : lenovo, data access, big data, data analysis
     Lenovo
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
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
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.
Tags : marketing cloud, target, big data, brands, customers, social media, smartphones, always-on
     ExactTarget
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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