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learning, conceptualizing + communicating data with infographics, visualizations, etc...
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Big Data Techniques for Analyzing Large Data Sets – Infographic

Big Data Techniques for Analyzing Large Data Sets – Infographic | visual data | Scoop.it

Until the emergence of “Big Data”, data were mainly treated locally in warehouses of several structured databases. Gradually, these data sources became diversified.


Analysts are projecting the future of customer data. Several points of attention are highlighted. While most companies collect, store and analyze data, majority of them are struggling with their big project data and are struggling to meet IT challenges associated with the use of this framework.


Newscientis, with Microsoft, released an infographic on how big data techniques seek to gain insight by analyzing large data sets. The proliferation of sources associated with 3V (volume, variety, velocity) have contributed to big data’s recent growth. Data is coming in a growing variety of new and often unstructured forms such as text, video and sensor reading.

By 2020, all the digital data created, replicated and consumed per year will reach 40,000 Exabytes. The connected devices including pocket calculators, personnel computer, mobile phones, servers and mainframes and videogame consoles have contributed more than 10 million instructions per second.

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Visualizing Databases | Digital Humanities Specialist

Visualizing Databases | Digital Humanities Specialist | visual data | Scoop.it

Summaries and statistics drawn from within the structure of the database are not enough. If there is to be any real grappling with the database as an culturally-embedded construct, then it has to be done in a manner that reveals the data, the model and the population simultaneously.

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luiy's curator insight, March 25, 2013 6:11 AM

I’ve become quite the fan of Gephi, lately, and received a good-natured challenge by one of my colleagues, which went something like, “Why is a everything a network with you, now?”  Obviously, in the case of social network-like phenomena, such as mapping collaboration in the Digital Humanities with the DH@Stanford graph–network theory and network language (whether visual or theoretical) make sense.  Network analytical tools like Gephi are also only a short step away from spatial analytical tools, like ArcGIS, many of which are used to ask questions about geographic networks and not about the kind of continuous data found in topography.

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Big Data Right Now: 5 Open Source Technologies

Big Data Right Now: 5 Open Source Technologies | visual data | Scoop.it

Big Data is on every CIO’s mind this quarter, and for good reason. Companies will have spent $4.3 billion on Big Data technologies by the end of 2012.
But here’s where it gets interesting.

Those initial investments will in turn trigger a domino effect of upgrades and new initiatives that are valued at $34 billion for 2013- over a 5 year period, spend is estimated at $232 billion. What we’re seeing right now is only the tip of a gigantic iceberg.


Read the original article for a closer 'look at five new technologies that are shaking things up in Big Data- the newest class of tools that you can’t afford to overlook...'

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