visual data

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Published By: Neo Technology     Published Date: Jun 28, 2015
The future of Master Data Management is deriving value from data relationships which reveal more data stories that become more and more important to competitive advantage as we enter into the future of data and business analytics. MDM will be about supplying consistent, meaningful views of master data and being able to unify data into one location, especially to optimize for query performance and data fit. Graph databases offer exactly that type of data/performance fit. Use data relationships to unlock real business value in MDM: - Graphs can easily model both hierarchical and non-hierarchical master data - The logical model IS the physical model making it easier for business users to visualize data relationships - Deliver insights in real-time from data relationships in your master data - Stay ahead of the business with faster development Download and read the white paper Your Master Data Is a Graph: Are You Ready? to learn why your master data is a graph and how graph databases like Neo4j are the best technologies for MDM.
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database, nosql, graph database, big data, master data management, mdm
    
Neo Technology
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: Attunity     Published Date: Sep 21, 2018
Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It provides an end-to-end platform that can collect, curate, analyze, and act on data in real-time, on-premises, or in the cloud with a drag-and-drop visual interface. This book offers you an overview of NiFi along with common use cases to help you get started, debug, and manage your own dataflows.
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Attunity
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: 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: Intel     Published Date: Feb 28, 2019
Keeping the lights on in a manufacturing environment remains top priority for industrial companies. All too often, factories are in a reactive mode, relying on manual inspections that risk downtime because they don’t usually reveal actionable problem data. Find out how the Nexcom Predictive Diagnostic Maintenance (PDM) system enables uninterrupted production during outages by monitoring each unit in the Diesel Uninterrupted Power Supplies (DUPS) system noninvasively. • Using vibration analysis, the system can detect 85% of power supply problems before they do damage or cause failure • Information processing for machine diagnostics is done at the edge, providing real-time alerts on potential issues with ample of lead time for managers to rectify • Graphic user interface offers visual representation and analysis of historical and trending data that is easily consumable
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Intel
Published By: MicroStrategy     Published Date: Jan 23, 2019
A&BI platforms are evolving beyond data visualization and dashboards to encompass augmented and advanced analytics. Data and analytics leaders should enable a broader set of users with new expanded capabilities to increase the business impact of their investments.
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MicroStrategy
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: 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 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
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. 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.
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TIBCO Software APAC
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: 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: 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: NetApp     Published Date: Sep 21, 2017
A visual infographic highlighting the five architectural principles of developing the Next Generation Data Center (NGDC), including scale-out, guaranteed performance, automated management, data assurance, and global efficiencies. This infographic typically accompanies the white paper, Designing the Next Generation Data Center, which is more in-depth account of the 5 principles.
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netapp, database performance, flash storage, data management, cost challenges, data
    
NetApp
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: CA Technologies EMEA     Published Date: Aug 07, 2017
One way to shift testing practices earlier in your software lifecycle is by using multi-layered visual models to specify requirements in a way where all ambiguity is inherently removed. With unambiguous and complete requirements, developers introduce less defects into their code and manual test cases, automated test scripts and required test data can be automatically generated based on the requirement, without manual intervention.
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data manager, data requirements, test automation, service virtualization, risk manager, continuous testing, testing effort, delivery ecosystem
    
CA Technologies EMEA
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: 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
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