data analytics

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Published By: Pure Storage     Published Date: Oct 09, 2017
Storing data is critical. Everyone stores data. Today, it’s all about how you use the data you’re storing and if you’re storing the right data. The right mix of data and the ability to analyze it against all data types is driving markets worldwide in what is known as digital transformation. Digital transformation requires storing, accessing, and analyzing all types of data as fast and efficiently as possible. The end goal is to derive insights and gain a competitive advantage by using those insights to move faster and deliver smarter products and services than your competition.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Pure Storage
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: Qlik     Published Date: Aug 12, 2015
This Research Report examines the analytical strategies of organisations currently using data discovery tools and highlights their superior performance in user engagement.
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data discovery, data, data discovery tools, analytics, benefits of using data discovery, data collaboration, data proliferation, data engagement, big data, data strategies
    
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: Hitachi Vantara     Published Date: Aug 16, 2018
In this infographic, we are going to show you the possibilities with modernized, optimized data infrastructure. In doing so, we aim to bring you ideas about how you can bring your own data-driven business vision to life, focusing on the outcomes that matter most to you. In essence, we will be discussing five main industries and the possibilities for modernized data infrastructure. We will be displaying how Banking and Financial Services, Telecommunications, Manufacturing, Healthcare and Retail can use data, analytics and automation to optimize their business, therefore bringing about a competitive edge which previously appeared unimaginable. Using data correctly, most importantly building proper data infrastructures, can be the driving force behind obtaining a competitive edge. Data is your story. And it’s our story, too.
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Hitachi Vantara
Published By: RelayHealth     Published Date: Apr 01, 2013
RelayHealth's Vice President, Business Analytics, Jason Williams examines how healthcare organizations can better set strategies by focusing on key decision points and adding data from real-time sources to what they have already collected.
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ecosystem, healthcare, real-time data, data, analysis, decision making, business analytics
    
RelayHealth
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: Logi Analytics     Published Date: Jan 12, 2016
This informative white paper highlights analytics tools, placing utmost importance on correctly enabling embedded analytics for competitive advantage.
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embedded analytics, analytic tools, analytics, data, collect data, reports
    
Logi Analytics
Published By: Logi Analytics     Published Date: Jan 12, 2016
Access this resource for the top 10 reasons why embedded analytics will bolster your existing business applications, and see real ways your operations can benefit from such insights.
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embedded analytics, analytic tools, analytics, data, collect data, reports
    
Logi Analytics
Published By: IBM     Published Date: Feb 02, 2016
Read this white paper to get an in-depth look at the benefits of embracing a digital business model, and find out how sports teams of all types can use cloud service providers with digital marketing and analytics tools to gain a competitive edge on the marketing playing field.
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ibm, sports, marketing, data, analytics, digital marketing
    
IBM
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: Feb 02, 2016
Read this report to gain more insights from the Telecoms.com Intelligence survey, and learn why telecommunications operators need analytics to understand their customers—and maintain their loyalty.
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ibm. telecom, data, analytics, customer management, customer loyalty
    
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
Published By: IBM     Published Date: May 17, 2016
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
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ibm, big data, inline analytics, business analytics, roi
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
This ebook 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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ibm, database, database change, analytics
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base. 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-centric 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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customer analytics, data matching, big data, competitive advantage, customer loyalty
    
IBM
Published By: IBM     Published Date: Jun 16, 2015
An IBM white paper describing the infrastructure implications of today’s converging technology forces and the software defined, next-generation data center transformation vital to capitalizing on them.
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enterprise infrastructure, big data, mobility, data center, it infrastructure, it security technologies, virtualizing infrastructure, converging technologies, analytics
    
IBM
Published By: IBM     Published Date: Jun 16, 2015
Read the white paper to learn how a good data center strategy can help you prepare for the rigors and unpredictability of emerging technologies. Find out how IBM’s predictive analytics are helping companies build more accurate, forward-looking data center strategies and how those strategies are leading to more agile, efficient and resilient infrastructures.
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data center, predictive analytics, data center strategy, resilient infrastructure, cloud computing, social collaboration, business analytics, emerging technologies, virtualization, automation
    
IBM
Published By: IBM     Published Date: Jan 27, 2016
Forrester Research evaluated 13 big data predictive analytics solution vendors and IBM emerged as one of the three leaders. Learn why.
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ibm, forrester wave, big data, predictive analytics
    
IBM
Published By: IBM     Published Date: May 16, 2016
Our objective in this Checklist Report is to share best practices that will position the reader to take advantage of a cloud-based data warehousing solution.
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ibm, tdwi, checklist report, data warehousing, cloud, analytics, analytic architecture, warehousing
    
IBM
Published By: IBM     Published Date: May 16, 2016
The data-driven organization is the new benchmark for success. Firms that harness data to dictate strategic and tactical decisions companywide make more informed business plans, better optimize operations, improve customer interactions, and provide competitive edge. To achieve these benefits, organizations increasingly see data refinement - transforming raw data from various sources into relevant and actionable information and delivering it through self - service access to any user who needs it - as the path toward success by helping break though immature processes and legacy systems. However, data refinement only functions as well as the strategies and approaches behind it. Organizations that do not understand the right way to embrace refinement will fail to catch up to competitors that have mastered the correct approach.
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ibm, forrester, data-driven organization, data, analytics, analytic architecture
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
The growing need for organizations to treat information as an asset is making metadata management strategic, driving significant growth for metadata management solutions. We evaluate nine vendors to help data and analytics leaders find the solution that best suits the needs of their organization.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection, metadata, business meta data, market data
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Today, all consumers can obtain any piece of data at any point in time. This experience represents a significant cultural shift: the beginning of the democratization of data. However, the data landscape is increasing in complexity, with diverse data types from myriad sources residing in a mix of environments: on-premises, in the cloud or both. How can you avoid data chaos?
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
Learn from this TDWI paper how right-sized information governance can improve the success of data warehousing or big data analytics initiatives, and how a chief data officer can help organizations to appreciate the value of data and its importance to their decisions and operations.
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system integration, data governance, data optimization, data efficiency, data currency, data lineage, data security, data integration
    
IBM
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