visual data
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visual data
learning, conceptualizing + communicating data with infographics, visualizations, etc...
Curated by Lauren Moss
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[INFOGRAPHIC] BIG DATA: What Your IT Team Wants You To Know

[INFOGRAPHIC] BIG DATA: What Your IT Team Wants You To Know | visual data |

The purpose of Big Data is to supply companies with actionable information on any variety of aspects. But this is proving to be far more difficult than it looks with over half of Big Data projects left uncompleted.

Two of the most often reported reasons for project failures are a lack of expertise in data analysis. Reports show that data processing, management and analysis are all difficult in any phase of the project, with IT teams citing each of those reasons more than 40% of the time.

However, failures in Big Data projects may not solely lie on faulty project management. In a recent survey, a staggering 80% of Big Data’s biggest challenges are from a lack of appropriate talent. The field’s relative infancy is making it hard to find the necessary staff to see projects through, resulting in underutilized data and missed project goals.

IT teams are quickly recognizing a chasm between executives and frontline staffers whose job it is to apply findings from Big Data. In the end,it may not be the anticipated cure-all for 21st century business management. It is only as good as good as the system that runs it.

Via Peter Azzopardi, Berend de Jonge
Olivier Vandelaer's curator insight, January 30, 2013 2:45 AM

Looking at the infographic, it clearly reminds me about the start of "Enterprise Data Warehouse": failures by "Innacurate scope", "Technical Roadblocks" & "Siloed data and no collaboration". It looks so familiar.

Tony Agresta's curator insight, January 30, 2013 10:15 AM

Very interesting infographic.  Why do they fail?  For all of the reasons above and then some...    Over 80% of the data being collected today is unstructured and not readily stored in relational database technology burdened by complex extract, transform and load.  There's also pre-existing data, sometimes referred to as "dark data" that includes documents which need to be included and made discoverable for a host of reasons - compliance and regulatory issues are one.   Log activity and e-mail traffic used to detect cyber threats and mitigate risk through analysis of file transfers is yet another set of data that requires immediate attention.


Social and mobile are clearly channels that need to be addressed as organizations continue to mine data from the open web in support of CRM, product alerts, real time advertising options and more.  


To accomplish all of this, organizations need a platform with enterprise hardened technology that can ingest all of these forms of data in real time, without having to write complex schemas.   Getting back to the point - What do most projects fail?   If companies attempt to do this with technology that is not reliable, not durable and does not leverage the skills of their existing development organization, the project will fail.  


We have seen this time and time again.   MarkLogic to the rescue.   With over 350 customers and 500 big data applications, our Enterprise NoSQL approach mitigates the risk.  Why?  Our technology stack includes connectors to Hadoop, integration with leading analytics tools using SQL, Java and Rest APIs, JSON support, real time data ingestion, the ability to handle any form of data, alerting, in database analytics functions, high availability, replication, security and a lot more.  


When you match this technology with a world-class services organization with proven implementation skills, we can guarantee your next Big Data project will work.  We have done it hundreds of times with the largest companies in the world and very, very big data.

Adrian Carr's curator insight, January 30, 2013 10:27 AM

This is a great infographic - it shows that whilst everyone is doing it (it being "Big Data" - whatever that is...), talent is rare, technology is hard to find and the projects never end.  A far cry from the speed with which companies such as the BBC deployed MarkLogic to serve all data for the sport websites through the Olympics.  Now that was big data, delivered by a talented team in a short space of time.

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2 GE Infographics Offer Hints About The Future Of Data-Driven Management

2 GE Infographics Offer Hints About The Future Of Data-Driven Management | visual data |
GE has been riding the infographics train for all its worth, creating a slew of remarkable charts illustrating everything from health ailments and how their linked to how good different countries are at innovating.

But they’ve rarely turned the lens onto the company’s own data, which makes these two experiments, by Ben Fry’s company Fathom, so interesting. Both look deep into the welter of data that GE’s products create everyday, and in so doing, offer a little glimpse into what could be possible when infographics make their way from Internet fad to management tool.

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Big Data Management for Marketing Effectiveness

Big Data Management for Marketing Effectiveness | visual data |

Big data in marketing world is also on the rise. Consider these stats: 4.8 trillion online ad impressions in 2011 and the predicted online ad spending of $83.2 billion for 2012. With the growth of unstructured data reach the 80 percent mark – also with the fact that there are 2.5 exabytes of data created on daily basis – those figures will only mean that big data is, indeed, big opportunities for businesses that are able to make the most of them.

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Open Source Intelligence Meets Real-Time News and Data Curation: SwiftRiver

Open Source Intelligence Meets Real-Time News and Data Curation: SwiftRiver | visual data |

SwiftRiver is a free and open-source intelligence platform that helps people curate and make sense of large amounts of information in a short amount of time.

In practice, SwiftRiver enables the filtering and verification of real-time data from channels such as SMS, email, Twitter and RSS feeds. It's especially useful for organizations that need to sort their data by their unique expectations of authority and accuracy, as opposed to popularity.


SwiftRiver allows you to discover, filter and present the information you want.

In SwiftRiver, these are "droplets." For example, common droplets in the river are tweets, Facebook updates, and blog posts. SwiftRiver determines all its attributes- for example, it can determine location, time, author and meaning (in the form of keywords) from a tweet. Once all the droplets are analyzed, you have the ability to filter them from a torrential river to a manageable stream.


Types of stories / output formats:

Graphs, Charts, Heatmaps
Gallery: Photos, Video, Audio

Via Robin Good, Howard Rheingold
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