data visualization

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Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
Published By: Alation     Published Date: Mar 15, 2016
curation (noun): The act of organizing and maintaining a collection (such as artworks, artifacts, or data). Data curation is emerging as a technique to support data governance, especially in data-driven organizations. As self-service data visualization tools have taken off, sharing the nuances and best practices of how to use data becomes ever more critical. Analysts at companies from eBay to Safeway and Square are scaling their data knowledge through curation techniques. What are the 4 steps to successful data curation? Find out here:
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data stewardship, self-service analytics, data curation, data governance
    
Alation
Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
Published By: SAS     Published Date: Jan 17, 2018
What can you see and discover when you’re able to explore trends and make predictions with your organization’s data? If you’re a midsize home delivery business, you can discover new ways to make customers happy. If you’re a local government agency, you can predict where your resources are needed most. And if you’re a growing hospital, you can bring life-changing patient data directly to doctors and nurses. In this e-book, we’ve profiled six organizations that are using self-service visual exploration to make big improvements in the way they work. From college administrators to professional sports teams, everyone makes better decisions with easy access to powerful, interactive analytics.
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SAS
Published By: SAS     Published Date: Jan 17, 2018
A picture is worth a thousand words – especially when you are trying to find relationships and understand your data – which could include thousands or even millions of variables. To create meaningful visuals of your data, there are some basic tips and techniques you should consider. Data size and composition play an important role when selecting graphs to represent your data. This paper, filled with graphics and explanations, discusses some of the basic issues concerning data visualization and provides suggestions for addressing those issues. From there, it moves on to the topic of big data and discusses those challenges and potential solutions as well. It also includes a section on SAS® Visual Analytics, software that was created especially for quickly visualizing very large amounts of data. Autocharting and "what does it mean" balloons can help even novice users create and interact with graphics that can help them understand and derive the most value from their data.
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SAS
Published By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking, it management, knowledge management, data management
    
Pentaho
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: SAS     Published Date: Nov 04, 2015
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management, data management
    
SAS
Published By: TreasureData     Published Date: May 14, 2012
Treasure Data is going to change the way that you think about Big Data and Cloud Data Warehousing. We'd like to get your input on how you see Big Data and Cloud Data Warehousing. Please take our 10 question survey and give us your input.
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treasuredata, data warehousing, cloud, big data, solution, data-driven, tables, queries, analytics, infrastructure, storage, billing, visualization, data management, virtualization, cloud computing, design and facilities
    
TreasureData
Published By: Oracle     Published Date: Nov 14, 2016
This webinar shows how to get instant clarity with stunningly visual analysis and self-service discovery using Data Virtualization Cloud Service.
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marketing analytics, cloud, cloud computing, virtualization, cloud service, cloud, analytics, oracle, infrastructure management
    
Oracle
Published By: Oracle     Published Date: Nov 14, 2016
Finding the signals in data has long been the realm of a select few. Not anymore. For one thing, it’s impossible for a small group of people to keep up with the amount of data that’s available, just as it’s impossible to keep up with the number of questions people want to answer.
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Oracle
Published By: Oracle Analytics     Published Date: Oct 06, 2017
Business decision making is undergoing a data-infused renaissance. Organizations are tired of the limitations of spreadsheets and dealing with long IT business intelligence (BI) development cycles just to gain access to the data they need now. Fortunately, with the advent of visual analytics and discovery tools (many offered in the cloud), the journey to data insight is getting simpler and faster. Rather than trying to divine meaning from a group of predefined reports or simple static dashboards, visual analytics helps users gain insights from data more quickly using intuitive data visualization. Increasingly, visual analytics tools provide easy-touse data preparation features for better data access. They support collaboration, mashups, and storytelling. TDWI Research sees growing interest in applying more modern, up-to-date tools for working with data.
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Oracle Analytics
Published By: Oracle Analytics     Published Date: Oct 10, 2017
How are organizations balancing self-service analytics and data governance today? What are the trends for tomorrow? Many organizations are on their way to achieving self-service analytics maturity through the use of intuitive data visualization technologies aimed at non-technical users; as well as various tactics that reduce reliance on IT. But handing the analytics reins entirely to business users can make governance nearly impossible. As a result, organizations are increasing investments in modern analytics platforms that enable a balance between IT governing and curating data, empowering business users to derive insights from data mostly on their own and without delay. Join guest speaker, Forrester Research VP and Principal Analyst, Boris Evelson and Oracle Analytics Senior Group Director, Jose Villacis as they discuss insights from an Oracle-commissioned study of North American enterprise analytics leaders.
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Oracle Analytics
Published By: Oracle Analytics     Published Date: Oct 10, 2017
How are organizations balancing self-service analytics and data governance today? What are the trends for tomorrow? Many organizations are on their way to achieving self-service analytics maturity through the use of intuitive data visualization technologies aimed at non-technical users; as well as various tactics that reduce reliance on IT. But handing the analytics reins entirely to business users can make governance nearly impossible. As a result, organizations are increasing investments in modern analytics platforms that enable a balance between IT governing and curating data, empowering business users to derive insights from data mostly on their own and without delay.
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Oracle Analytics
Published By: TIBCO Software APAC     Published Date: Aug 13, 2018
TIBCO Spotfire is the premier data discovery and analytics platform, which provides powerful capabilities for our customers, such as dimension-free data exploration through interactive visualizations, and data mashup to quickly combine disparate data to gain insights masked by data silos or aggregations.
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: May 31, 2018
Ask the average business user what they know about Business Intelligence (BI) and data analytics, and most will claim to understand the concepts. Few, however, will profess to know how analytics works or to have the skills needed to put it into practice. Despite being knowledgeable about their industry and experienced in running their organizations, the majority of business users lack expertise in analytics and visualization techniques—but that doesn’t stop them from wanting to have a go. This situation has led to ease of use and accessibility becoming the main focus for recent updates from all the leading BI vendors—but making tools easier and more widely accessible is only part of the answer. A better approach is to work both sides of the gap. To make tools that can empower business users to discover and unlock value in their data—and that extend capabilities for experts, so they can share the analytics workload, improve efficiency, and focus on higher level work. Unfortunately, the
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TIBCO Software APAC
Published By: Waterline Data & Research Partners     Published Date: Jun 15, 2015
This analysis profiles products that can accelerate the shift toward business-user-oriented, visual, interactive data preparation.
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gartner, analysis, data visualization, business tools, best practices, interactivity, vendor functionality
    
Waterline Data & Research Partners
Published By: Oracle     Published Date: Nov 14, 2016
Short demo showing how Oracle Data Visualization can be used to combine Project Cost and Resourcing data with HR Recruitment data.
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Oracle
Published By: Oracle     Published Date: Nov 14, 2016
Durante mucho tiempo, distinguir las señales inmersas en una masa de datos era el privilegio de pocos. Ya no es el caso. Hoy es imposible que un pequeño grupo de personas gestione el volumen de datos disponibles, así como es imposible imaginar todas las preguntas que necesitan una respuesta.
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Oracle
Published By: Oracle     Published Date: Nov 14, 2016
Savoir déceler les signaux enfouis dans une masse de données a longtemps été l'apanage d'un petit nombre. Plus maintenant. Aujourd'hui, il n'est plus possible pour un petit groupe de personnes de gérer le volume de données disponibles, tout comme il est impossible d'imaginer toutes les questions auxquelles les gens veulent une réponse.
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Oracle
Published By: Oracle     Published Date: Nov 14, 2016
Saper estrarre le informazioni salienti da una massa è stata per molto tempo una prerogativa di pochi. Ora non più. Oggi non è più possibile per un piccolo gruppo di persone gestire il volume di dati disponibili, come non è più possibile immaginare tutte le domande a cui si vuole trovare risposta.
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Oracle
Published By: Qlik     Published Date: Oct 13, 2015
Read more to learn how modern companies are adjusting to the BYO (Bring Your Own) data trend by combining external data with internal content.
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qlik, data discovery, business intelligence, analytics, user produced content, cloud, social, data visualization, external data, internal content, data management, business technology, data center
    
Qlik
Published By: Qlik     Published Date: Oct 13, 2015
Read more to learn how IT ensures that they are empowering their users with the tools they need to naturally explore data, ask the next question, and uncover the insight they need to make informed decisions.
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qlik, data discovery, business intelligence, analytics, user produced content, cloud, social, data visualization, big data, mobile, data management, business technology, data center
    
Qlik
Published By: IBM     Published Date: Jan 11, 2017
Download this eBook to learn: - How the use of advanced analytics generates powerful insights to stay ahead of evolving cyber threats - Why Cyber Threat Analysis is the most effective defensive strategy - How analysts benefit from the use of sophisticated data visualization to identify hidden threat relationships and patterns - Why shifting from attack prevention to mitigation is a more practical goal for commercial organizations
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ibm, analytics, public sector, security, cyber threat, cyber threat analysis, risk, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Jun 04, 2018
"Today’s business users want to use all types of data to create compelling, shareable visualizations. But charts and graphs alone may not convey all the information, especially when they are part of a complex series. An audience can best understand analytic results when those results tell a story that connects all the pieces together. The right visuals can also reinforce the lessons buried in the data. Stories are powerful mechanism to communicate with people. Stories stick and make insights actionable, so it goes without saying that storytelling is a very powerful (soft) skill. In this webinar, you'll learn how to effectively apply storytelling best practices to get your message across. Especially in the world of BI, it is getting more and more important to effectively communicate business results. Watch this webinar to learn how to use IBM Cognos Analytics to: · Create the important elements of a good story · Put the data in context · Select the best type of ch
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data analytics, data storytelling, business intelligence
    
IBM
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