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Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: Mimecast     Published Date: Apr 18, 2017
"Your Email & The EU GDPR GDPR changes how organizations need to protect personal data, including data contained in email and contact databases. Regardless of physical location, you must be in GDPR compliance for EU resident personal data by May 2018. Download the white paper to learn: - The unprecedented level of effort required for collecting and processing personal data - The specific security, privacy and protection requirements to comply with GDPR - How a majority (58%) of mid-sized and large organizations have a poor understanding of the wide scope of the regulation and associated penalties"
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gdpr, email, personal data, security, data protection
    
Mimecast
Published By: MemSQL     Published Date: Nov 15, 2017
FREE O'REILLY EBOOK: BUILDING REAL-TIME DATA PIPELINES Unifying Applications and Analytics with In-Memory Architectures You'll Learn: - How to use Apache Kafka and Spark to build real-time data pipelines - How to use in-memory database management systems for real-time analytics - Top architectures for transitioning from data silos to real-time processing - Steps for getting to real-time operational systems - Considerations for choosing the best deployment option
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hardware trends, data pipelines, database management, architectures, technology
    
MemSQL
Published By: MemSQL     Published Date: Nov 15, 2017
The Path to Predictive Analytics and Machine Learning This Ebook will be your guide to building and deploying scalable, production-ready machine-learning applications. Inside, you will find several machine learning use cases, code samples to help you get started, and recommended data processing architectures.
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data pipelines, analytics, database, machine learning
    
MemSQL
Published By: MemSQL     Published Date: Nov 15, 2017
Data Warehousing in the Age of Artificial Intelligence This Ebook will guide you through building and deploying scalable, production-ready artificial-intelligence applications. Inside, you will find several artificial intelligence use cases, code samples to help you get started, and an outline of high throughput data processing architectures necessary for developing AI applications.
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data warehousing, artificial intelligence, data piplelines
    
MemSQL
Published By: NEC     Published Date: Sep 29, 2009
Written by: IDC Abner Germanow, Jonathan Edwards, Lee Doyle IDC believes the convergence of communications and mainstream IT architectures will drive significant innovation in business processes over the next decade.
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it architecture, idc, automation, automated order processing, soa, service oriented architecture, soap, http, xml, wsdl, uddi, esbs, jee, .net, crm, san
    
NEC
Published By: Vision Solutions     Published Date: Feb 18, 2008
Continuous member service is an important deliverable for credit unions, and. the continued growth in assets and members means that the impact of downtime is affecting a larger base and is therefore potentially much more costly. Learn how new data protection and recovery technologies are making a huge impact on downtime for credit unions that depend on AIX-hosted applications.
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vision, high availability, ibm, aix, cdp, core union
    
Vision Solutions
Published By: SAP     Published Date: Feb 03, 2017
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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SAP
Published By: SAP     Published Date: Feb 03, 2017
The spatial analytics features of the SAP HANA platform can help you supercharge your business with location-specific data. By analyzing geospatial information, much of which is already present in your enterprise data, SAP HANA helps you pinpoint events, resolve boundaries locate customers and visualize routing. Spatial processing functionality is standard with your full-use SAP HANA licenses.
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SAP
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: SAP     Published Date: May 18, 2014
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
    
SAP
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
In midsize and large organizations, critical business processing continues to depend on relational databases including Microsoft® SQL Server. While new tools like Hadoop help businesses analyze oceans of Big Data, conventional relational-database management systems (RDBMS) remain the backbone for online transaction processing (OLTP), online analytic processing (OLAP), and mixed OLTP/OLAP workloads.
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database usage, database management, server usage, data protection
    
Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
What if you could reduce the cost of running Oracle databases and improve database performance at the same time? What would it mean to your enterprise and your IT operations? Oracle databases play a critical role in many enterprises. They’re the engines that drive critical online transaction (OLTP) and online analytical (OLAP) processing applications, the lifeblood of the business. These databases also create a unique challenge for IT leaders charged with improving productivity and driving new revenue opportunities while simultaneously reducing costs.
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cost reduction, oracle database, it operation, online transaction, online analytics
    
Hewlett Packard Enterprise
Published By: Cisco     Published Date: Jun 21, 2016
The Cisco® Hyperlocation Solution is the industry’s first Wi-Fi network-based location system that can help businesses and users pinpoint a user’s location to within one to three meters, depending on the deployment. Combining innovative RF antenna and module design, faster and more frequent data processing, and a powerful platform for customer engagement, it can help businesses create more personalized and profitable customer experiences.
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Cisco
Published By: Pentaho     Published Date: Feb 26, 2015
This eBook from O’Reilly Media will help you navigate the diverse and fast-changing landscape of technologies for processing and storing data (NoSQL, big data, MapReduce, etc).
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data systems, data-intensive applications, scalability, maintainability, data storage, application development
    
Pentaho
Published By: OpenText     Published Date: Mar 02, 2017
Watch the video to learn how Procure-to-Pay (P2P) solutions automate B2B processes to help you gain better visibility into transaction lifecycles, improve efficiency, and increase the speed and accuracy of order, shipping, and invoice processing.
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supply chain, b2b, procure-to-pay, shipping, invoicing
    
OpenText
Published By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: IBM APAC     Published Date: Nov 22, 2017
Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.
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decision making, deeper data, insights, cognitive, analytics, ibm, watson, virtual agents
    
IBM APAC
Published By: IBM APAC     Published Date: Nov 22, 2017
AlchemyAPI’s approach to natural language processing incorporates both linguistic and statistical analysis techniques into a single unified system. This hybrid approach provides an industry-leading advantage since both techniques have benefits and drawbacks depending on the content and specific usecases. Linguistic analysis takes a basic grammatical approach to understand how words combine into phrases, and how those phrases combine into sentences. While this approach works well with editorialized text (e.g., news articles and press releases), it does not perform as well when it comes to usergenerated content, often filled with slang, misspellings and idioms. Statistical analysis, however, understands language from a mathematical standpoint and works well on “noisy” content (e.g., tweets, blog posts, and Facebook status updates). The combination of these two approaches allows for increased accuracy on a variety of content.
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industry, advantage, linguistic, grammatical, statistical analysis, content
    
IBM APAC
Published By: Digital Realty     Published Date: Feb 25, 2015
When measuring competitive differentiation in milliseconds, connectivity is a key component for any financial services company’s data center strategy. In planning the move of its primary data center, a large international futures and commodities trading company needed to find a provider that could deliver the high capacity connectivity it required.
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financial services, trade processing, data center, connectivity, data center
    
Digital Realty
Published By: Dell EMC     Published Date: Nov 02, 2015
Today’s IT environment is more complex than ever. The applications that have become critical to business operations require greater processing power, memory, and storage. This guide prepares decision-makers to choose servers that meet their current needs, while building a flexible, reliable, scalable infrastructure to handle future requirements.
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Dell EMC
Published By: Dell EMC     Published Date: Nov 09, 2015
This business-oriented white paper summarizes the wide-ranging benefits of the Hadoop platform, highlights common data processing use cases and explores examples of specific use cases in vertical industries. The information presented here draws on the collective experiences of three leaders in the use of Hadoop technologies—Dell and its partners Cloudera and Intel.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
Big data can be observed, in a real sense, by computers processing it and often by humans reviewing visualizations created from it. In the past, humans had to reduce the data, often using techniques of statistical sampling, to be able to make sense of it. Now, new big data processing techniques will help us make sense of it without traditional reduction.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 12, 2015
This business-oriented white paper explains four options for starting your Hadoop journey. This paper also outlines the benefits of Hadoop and highlights some of the many use cases for this new approach to managing, storing and processing big data.
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Dell EMC
Published By: SAS     Published Date: Apr 16, 2015
Former Intel CEO Andy Grove once coined the phrase, “Technology happens.” As true as Grove’s pat aphorism has become, it’s not always good news. Twenty years ago, no one ever got fired for buying IBM. In the heyday of customer relationship management (CRM), companies bought first and asked questions later. Nowadays, executives are being enlightened by the promise of big data technologies and the role data plays in the fact-based enterprise. Leaders in business and IT alike are waking up to the reality that – despite the hype around platforms and processing speeds – their companies have failed to established sustained processes and skills around data.
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SAS
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