big data analytics

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Published By: Oracle Analytics     Published Date: Oct 06, 2017
Empowered with mobile and cloud-based access to a myriad of products and services, customers now have a variety of options at their fingertips with regards to partnerships. Enterprises that do not follow the ever-changing tastes and preferences of their customers, or that wait too long to react, will fall behind and fail. Across functions, business professionals readily require big data tools and insights to understand and serve these customers. It is no longer an option for business users to rely on IT to deliver customer and other relevant analytics. On the flipside, handing the analytics reins entirely to business users can make governance nearly impossible. Organizations must find balance in a new approach in which IT mostly governs and curates data while business users are empowered to derive insights from data mostly ontheir own without delay.
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Oracle Analytics
Published By: IBM     Published Date: Jun 16, 2015
This paper explores the implications of cloud, big data and analytics, mobile, social business and the evolving IT security landscape on data center and enterprise networks and the changes that organizations will need to make in order to capitalize on these technology force.
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cloud computing, mobility, big data, business analytics, it security landscape, enterprise networks, cloud integration, virtualization
    
IBM
Published By: IBM     Published Date: Jul 07, 2015
This paper explores the implications of cloud, big data and analytics, mobile, social business and the evolving IT security landscape on data center and enterprise networks and the changes that organizations will need to make in order to capitalize on these technology force.
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the cloud, mobile, mobility, social, analytics, networks, enterprise network, big data, network infrastructure
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Smart on-line transaction processing systems will be able to leverage transactions and big data analytics on-demand, on an event-driven basis and in real-time for competitive advantage. Download to learn how!
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big data, operational decision making, transaction data
    
IBM
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
Learn how to create cloud infrastructure that's secure by default and has better core efficiency for Java, database, and big data. Oracle's servers offer hardware acceleration of data analytics and machine learning, with 10X better time-to-insight.
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Oracle PaaS/IaaS/Hardware
Published By: JBoss Developer     Published Date: Oct 21, 2016
Java applications have been a central technology for enterprises for two decades. This wealth of data, functionality, and knowledge are critical to enterprises. With Java-based applications, modern development can build on a platform that enables cloud-native architectures while simultaneously supporting existing applications. This combination of traditional enterprise-wide monoliths and cloud-based application deployment allows organizations to take advantage of existing knowledge and resources while actively moving toward newer application models.
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middleware, java, big data, analytics, mobile development
    
JBoss Developer
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: Teradata     Published Date: Jan 30, 2015
This TDWI Checklist Report discusses adjustments to DW architectures that real-world organizations are making today, so that Hadoop can help the DW environment satisfy new business requirements for big data management and big data analytics.
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data, data warehouse, hadoop, hadoop ecosystem, data architectures, data archiving, advanced analytics
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
Big Data analytics are a top priority at many companies today. Most hope to derive new insights from all available data to improve productivity, cut costs, reduce churn, enhance the customer experience, and seize new business opportunities.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
This report is about two of those architectures: Apache™ Hadoop® YARN and Teradata® Aster® Seamless Network Analytical Processing (SNAP) Framework™. In the report, each architecture is described; the use of each in a business problem is illustrated; and the results are compared.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, aster, snap, framework, apache, hadoop, yarn, architectures
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, framework, apache, hadoop, architecture, warehouse, optimization, security, scalability, consistency, flexibility
    
Teradata
Published By: Cisco     Published Date: Sep 16, 2015
Big data into manageable components.
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big data, data platform, ioe, analytics
    
Cisco
Published By: Progress     Published Date: Mar 06, 2017
The Digital Marketing Maturity Guide helps organizations determine the level of sophistication within their digital marketing operations. Dimensional Research to conducted a global survey of 700 marketing professionals gauging the level of digital marketing maturity across various verticals and company sizes. Use these findings to benchmark your organization against other groups.
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digital marketing, operations, big data, analytics, web content management, content management systems
    
Progress
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
Published By: RedPoint Global     Published Date: May 11, 2017
Practical perspectives on leveraging data to grow sales, cut costs, up-sell more effectively and make better decisions. Marketers overwhelmingly agree they have access to more than enough data. The problem is finding actionable ways to utilize data that is collected across all customer interaction points to better engage with customer and increase lifetime customer value. This white paper explores the relevance of big data for marketers: what they need to know and the steps they should take today to embrace data and analytics to position their organizations for success today.
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customer retention, customer experience, real-time personalization, customer insights
    
RedPoint Global
Published By: Oracle APAC ZO OD Prime Volume ERP ABM Leads June 2017     Published Date: Jul 12, 2017
Relentless digital developments have created the chance for the finance team to become true strategic leaders across the business—but they have also raised expectations and generated new challenges. In this digibook, we explore the growth of cloud, social, mobile and big data, and how smart CFOs are taking advantage. We show how to use your big data analytics and smooth procurement systems as a launchpad to holding your own in the Digital Age. Each chapter is illustrated by examples from successful businesses that have embraced the new ways of working as well as guidance on how to plan for and implement the changes that are right for you.
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data analytics, digital age, digital transformation, cloud, big data, growth
    
Oracle APAC ZO OD Prime Volume ERP ABM Leads June 2017
Published By: TIBCO Software APAC     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software APAC
Published By: Splunk     Published Date: Aug 21, 2018
SIEM (security information and event management) software offers a lot of promise, but legacy SIEMs simply can't keep up with the rate and sophistication of today's cyberattacks. Organizations today require access to analytics-driven SIEMs that combine a big data platform that is optimized for machine data with advanced analytics, threat detection, monitoring tools, incident response tools and multiple forms of threat intelligence. Download your complimentary copy of “The Six Essential Capabilities of an Analytics-Driven SIEM” and learn how to dramatically improve your security posture, advanced threat detection and incident response.
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Splunk
Published By: Attunity     Published Date: Jan 14, 2019
This whitepaper explores how to automate your data lake pipeline to address common challenges including how to prevent data lakes from devolving into useless data swamps and how to deliver analytics-ready data via automation. Read Increase Data Lake ROI with Streaming Data Pipelines to learn about: • Common data lake origins and challenges including integrating diverse data from multiple data source platforms, including lakes on premises and in the cloud. • Delivering real-time integration, with change data capture (CDC) technology that integrates live transactions with the data lake. • Rethinking the data lake with multi-stage methodology, continuous data ingestion and merging processes that assemble a historical data store. • Leveraging a scalable and autonomous streaming data pipeline to deliver analytics-ready data sets for better business insights. Read this Attunity whitepaper now to get ahead on your data lake strategy in 2019.
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data lake, data pipeline, change data capture, data swamp, hybrid data integration, data ingestion, streaming data, real-time data, big data, hadoop, agile analytics, cloud data lake, cloud data warehouse, data lake ingestion, data ingestion
    
Attunity
Published By: Qlik     Published Date: Aug 12, 2015
The Business Intelligence Survey provides you with well-designed KPI dashboards packed with concise information, which can be absorbed at a glance.
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business technology, qlik, data, big data, analytics, qlikviews, dashboard vendor
    
Qlik
Published By: Hitachi Vantara     Published Date: Aug 14, 2018
In this book, we are going to look at the key trends driving the modernization of data infrastructure. We’ll see how organizations are adapting and flourishing in a data-driven world. For some time, headlines have been around the internet of things (IoT), big data and data analytics. While these developments are important, the reality is that you cannot take full advantage of them without modernization. We’re going to look at these trends and priorities in detail, then look at the three key drivers of modernization: governance, mobilization and analytics. We’ll also consider the technologies that make up modern data infrastructure including artificial intelligence (AI), flash storage, converged and hyperconverged platforms and software-defined infrastructures. By making sense of data, we make sense of the world. With more data than ever before, we have the tools to turn all that information into intelligent innovation and change the way the world works.
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data infrastructure, big data, internet of things
    
Hitachi Vantara
Published By: Cisco     Published Date: Nov 18, 2015
In this playbook, we provide you with a framework to bring big data to your agency. We break down big data into manageable components to help you understand how to make big data a reality at your agency. Our guide will serve as a roadmap for innovation and provide you with step-by-step instructions to deploy big data at your agency.
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big data, data platform, ioe, analytics
    
Cisco
Published By: IBM     Published Date: Feb 02, 2016
Advanced analytics can provide extremelyvaluable insight into today’s media viewers. This must-read report details the top 10 best practices for successfully implementing data analytics for driving profit, attracting new viewers, and increasing viewer loyalty.
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ibm, big data, analytics, media, entertainment, data analytics
    
IBM
Published By: IBM     Published Date: May 17, 2016
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.
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ibm, intelligent business solutions, big data, transaction data, business analytics
    
IBM
Published By: IBM     Published Date: May 17, 2016
Is your data architecture up to the challenge of the big data era? Can it manage workload demands, handle hybrid cloud environments and keep up with performance requirements? Here are six reasons why changing your database can help you take advantage of data and analytics innovations. 
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ibm, business analytics, business intelligence, data, analytics, database
    
IBM
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