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Bioinformatics clouds for big data manipulation

As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.


Via Ashish Umre
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Cloud Expo New York: Best Practices for Big Unstructured Data Storage

Big Data has become very popular as what can probably best be described as “loosely structured large scale data”, i.e., data sets of relatively small files.

Via Patrick Bouillaud
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Hadoop Tuesdays: Get a Handle on Unstructured Data with a 7-part Webinar Series Led By Cloudera and Informatica

Cloudera offers enterprises a powerful new data platform built on the popular Apache Hadoop open-source software package. (RT @cloudera: More than 1,000 have registered for the #Hadoop Tuesday Webinars.

Via Armando Reis
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The wild west of work media: A deluge of streamed, unstructured data

The wild west of work media: A deluge of streamed, unstructured data | Big Data Venture Capital | Scoop.it

This article is one of the best I have read regarding the danger of "information silos" that are created when your company's collaboration website does not have a plan for creating a culture of sharing.


Via Ken Morrison
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AllAnalytics - Seth Grimes - Scouting the Next Frontiers for 'Unstructured' Data

AllAnalytics - Seth Grimes - Scouting the Next Frontiers for 'Unstructured' Data | Big Data Venture Capital | Scoop.it
Beyond text, lots of work remains in getting a handle on unstructured data.

Via M. Edward (Ed) Borasky
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The Rapid Growth in Unstructured Data

The Rapid Growth in Unstructured Data | Big Data Venture Capital | Scoop.it

It is projected that the amount of digital information that will be created in 2010 could fill 75 billion fully-loaded 16 GB Apple iPads.

 

Stacked on a field the size of Wembley Stadium, that "iStack" would reach height over 4 miles high; nearly 280,000 iPads in every layer.


Via Lauren Moss
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'Big data' strains, stresses real-time business intelligence systems

Adding big data to real-time business intelligence and analytics applications creates more complexity for BI teams looking to mix batch-oriented big data tools with real-time BI systems.

Via Ian Sykes
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Art Vancil's curator insight, January 21, 2013 9:54 AM

The do-it-yourself customers are beginning to temper the Big Data hype with reality, as they discover architecture limitations of their tools. Don't allow the hype to drive your architecture decisions until you have demonstrated that the tools will meet your requirements.

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Power of ideas: How startups growing sans venture capital money

Power of ideas: How startups growing sans venture capital money | Big Data Venture Capital | Scoop.it
ET take a look at some of the most popular strategies that startups have used to conserve and effectively use funds when the supply of venture capital is scarce. That it takes more than money to...
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Dundas Data Visualization Partners with IQPC for Call Center Summit - San Francisco Chronicle (press release)

Dundas Data Visualization Partners with IQPC for Call Center Summit - San Francisco Chronicle (press release) | Big Data Venture Capital | Scoop.it
Dundas Data Visualization Partners with IQPC for Call Center Summit San Francisco Chronicle (press release) Dundas Data Visualization is proud to be giving a presentation on Call Center Dashboards alongside partner Farmers Insurance at the 8th...
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Digital Humanities Initiative | Forum | Event of Interest: Data Visualization for Performing Arts & Cinema | CUNY Academic Commons

Digital Humanities Initiative | Forum | Event of Interest: Data Visualization for Performing Arts & Cinema | CUNY Academic Commons | Big Data Venture Capital | Scoop.it
I will be speaking at the "Data Visualization for Performing Arts & Cinema" in New York, Feb. 7 http://t.co/6WUuwzbw #digitalhumanities
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Introduction to Infographics and Data Visualization, January 2013

Introduction to Infographics and Data Visualization, January 2013 (Couldn't resist another online course - Introduction to Infographics and Data Visualization http://t.co/KQxnUpA4 #storytelling)...
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Which metro areas got the most venture capital in 2012

Which metro areas got the most venture capital in 2012 | Big Data Venture Capital | Scoop.it
Chicago remains in the outer orbit of the nation's venture-capital universe.
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Data-Visualization Firm's New Software Autonomously Finds Abstract Connections | Wired Design | Wired.com

Data-Visualization Firm's New Software Autonomously Finds Abstract Connections | Wired Design | Wired.com | Big Data Venture Capital | Scoop.it
Ayasdi, a company that has developed data-visualization software it says uses big data to answer the questions you never thought to ask, has launched in Palo Alto with $10.25 million in funding.
Bryan St.Laurent's insight:

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Big Data Apps: The Ultimate in Conversion Optimization

Big Data Apps: The Ultimate in Conversion Optimization | Big Data Venture Capital | Scoop.it

Big data is all the rage right now. Companies like Amazon and Facebook are finding innovative ways to turn massive amounts of data into strategic marketing decisions. Based on the amount of news coverage big data gets these days and the investments organizations have been making (see below), it is clear that big data is not simply a buzzword that will be dead next year.

 

With all the hype, it is important to start thinking about what this means for the non-Amazon’s of the world. As a search marketer, I work with clients that are still facing challenges in dealing with “small” data. And now they have to tackle big data?


Via Ashish Umre
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HP Blogs - Unstructured data analytics: The new gold mine - The HP Blog Hub

HP Blogs - Unstructured data analytics: The new gold mine - The HP Blog Hub | Big Data Venture Capital | Scoop.it
By Scott Walters, Business Solutions Leader, HP Enterprise Information Solutions, HP Enterprise Services   Unstructured data analytics is a gold mine of business intelligence.

Via Carla Gentry CSPO
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Electronic Health Records and the challenge of Unstructured Data | Medical Software Guides

Electronic Health Records and the challenge of Unstructured Data | Medical Software Guides | Big Data Venture Capital | Scoop.it
By Sheldon Needle The real problem of an established medical practice moving into the realm of EHR is not the cost of the medical software package; (Electronic Health Records and the challenge of Unstructured Data ...: By Sheldon Needle The real problem...

Via NY HealthScape
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Why Nobody Is Actually Analyzing Unstructured Data | SmartData Collective

Why Nobody Is Actually Analyzing Unstructured Data | SmartData Collective | Big Data Venture Capital | Scoop.it
Unstructured data has been a very popular topic lately since so many big data sources are unstructured.

Via M. Edward (Ed) Borasky
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MarkLogic® and Tableau Deliver Analytics and Visualization Over Unstructured Data | MarkLogic

Business users can now harness the power of Tableau’s award-winning business intelligence and reporting solutions to access disparate data sets of structured and unstructured data stored in a MarkLogic database.
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Mason Powers's curator insight, December 19, 2012 3:27 PM

Organizations are struggling to manage, and more importantly, extract valuable insights from unstructured data.  This webinar presents a solution to this problem, using technologies analysts already know, with a purpose-built technology in the background (MarkLogic's Enterprise NoSQL Database) that easily exposes all of your data (structured, semi, and unstructured), to Tableau's B.I. and reporting capabilities.

 

Streamlining operations while seamlessly delivering intelligence that is derived from ALL of your data, not just the "easy" data. 

Tony Agresta's comment, December 20, 2012 12:01 PM
If you missed this one, the replay will be available soon at www.marklogic.com. In the meantime, here are the Top 10 points made during the presentation plus a short description of the demo that was done. I’ll update this post with the link to the recording as soon as it’s available - 1) The "Value" of big data is essential – When it comes to analytics, this could easily be the 4th "V" in big data in addition to volume, velocity and variety. Analytics allows you to determine and apply value in your organization. 53% of the respondents on the webinar felt that data integration is the most significant challenge they face. 2 ) User adoption of analytical technology is driven by ease of use and robust functionality. Many software companies have struggled with this basic premise. Tableau has gotten it right creating competitive distinction and increasing customer satisfaction. 3) When combined with an Enterprise NoSQL approach that includes native Search capabilities, data can be exposed to Tableau in a highly scalable, secure environment that includes point in time recovery and real time ingestion, among other capabilities. 4) “Dark data” (data previously ignored by the enterprise) can now be monetized through unified information access and data visualization that provide “angles of analysis”. These angles reveal the value. In this context, “angles” refers to visualizations and interactivity allowing users to discover meaning. 5) Loading data “as is” using a schema-less database (and also search the data in real time) can dramatically shorten the cycles from data ingestion to decisions. This premise is especially important in mission critical applications across healthcare, government, financial services and media markets, to name a few. 6) Text mining tools provide context through “markup” that add value to the data. A big data solution that includes natural language processing and semantics can enhance that meaning and may be needed, depending on the data problem at hand. 7) Hadoop is now part of the MarkLogic platform allowing users to store the data and make it available to MarkLogic “on demand”. This staging area is important because of the sheer volume, velocity and variety of data coming in. 8) Visualization is the last key component of this big data technology stack and hence the partnership between MarkLogic and Tableau. 9) MarkLogic data is exposed to Tableau though ODBC. Data has been converted to XML and Tableau taps into the data. 10) Unstructured data can be blended with more traditional structured data on the Tableau side to provide a more complete picture of the data.
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Finding structure for unstructured data - FCW.com

Finding structure for unstructured data - FCW.com | Big Data Venture Capital | Scoop.it
Fort Mills Times
Finding structure for unstructured data
FCW.com
If hype equaled performance, big data and cloud computing would already be unmatched cost-cutting, efficiency-increasing, bottom line-building tools in the federal space.

Via Toni Sánchez, Tony Agresta
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Tony Agresta's curator insight, January 11, 2013 5:07 PM

There's a link to the paper entitled "Delivering on the Promise of Big Data in The Cloud" which goes into more detail on the Reference Data Architecture.   In that paper, the authors describe some of the techniques used to filter big data and visualize it in support of revealing meaning in the data.  Some of this visualization will involve charting, maps, timelines, tables and relationship graphs.  Big data is manageable given the right tools and methods of analysis.

 

When using this tools, here are some of the steps I've seen applied in the past with success -

 

  • Take an inventory of your data identifying data sources, tables, fields, missing values and the range of values for each field you will be working with.  How clean is the data?   Do you have what your need for the analysis?
  • Form your hypothesis and a detailed set of questions you want to answer about the data.  What are you trying to uncover?  What questions do you need to ask of the data?
  • Filter your data to arrive at a set of data to visualize.  This may need to be done in stages. For example, if you're using a visualization tool, you may be able to pre-process the data selecting a subset for your analysis. After some initial charting, you may identify a sub segment of data you want to look at more closely.  After looking at that data in different forms (maps, timelines, tables), you may decide it can be refined even further.
  • Use relationship graphing (link analysis) to connect the dots.   You may decide you need to see relationships between people and the flights they took, or people, where they live and where they work.  Any number of connection points can be analyzed with commercially available tools.   Too many connections will make the graph overly complex.   Three to six is probably ideal.
  • From that point, there are ways to highlight meaning in the data - scaling the size of the nodes and links based on other measures such as amount of deposits, number of calls, number of connections to other nodes – all of these will point you toward parts of the graph you need to explore in more detail.  Labeling and showing direction between the nodes (Did Jim call Steve or did Steve call Jim?) are other ways to analyze the data. 
  • Most tools that perform link analysis allow you to draw the graphs using different layouts. For example, draw the graph with the node that has the greatest number of connection points at the center.   Social network metrics like centrality and betweeness help you identify important nodes on the graph.  The entire space should be searchable providing you another level of filtering to identify individuals of interest.
  • There's usually a time dimension that's important in this type of analysis.  For example, when accounts were opened and closed, when phone calls were made or when flights were taken may provide additional insights.   Some tools allow you to build the graph based on this time dimension as if you're watching a movie. The graph is constructed based on these important events.
  • Share your results along with the insights you've found.  See if other analysts have additional things to add.

 

There are a ton of techniques you can use when it comes to big data visualization.    This is just a small sample but hopefully it helps analysts naviagte through large sets of data using data visualization and link analysis.

 


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Venture capital deals - The Term Sheet: Fortune's deals blogTerm ...

Venture capital deals - The Term Sheet: Fortune's deals blogTerm ... | Big Data Venture Capital | Scoop.it
Backers include AGF Investments, Pinetree Capital, Plazacorp Ventures and Cranson Capital. www.keek.com Abe's Market, a Buffalo Grove, Ill.-based website for discovering natural and organic products, has raised $5 ...
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PaaS Pivot: Big Data At The Core Of Platform Services

PaaS Pivot: Big Data At The Core Of Platform Services | Big Data Venture Capital | Scoop.it
Keep in mind that whatever we have seen so far with regards to “big data applications” are mostly focussed on analytics and visualization. What we are going to see in the future are set of services built on top of Intelligent ...
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Top Hat Monocle Adds $1.1M Follow-On From Felicis To Reimagine The Lecture ... - TechCrunch

Top Hat Monocle Adds $1.1M Follow-On From Felicis To Reimagine The Lecture ... - TechCrunch | Big Data Venture Capital | Scoop.it
Top Hat Monocle Adds $1.1M Follow-On From Felicis To Reimagine The Lecture ...
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Big Data is Vital to the Transformation of Healthcare Infographic

Big Data is Vital to the Transformation of Healthcare Infographic | Big Data Venture Capital | Scoop.it
Big data is vital to the transformation of healthcare infographic highlights how big data can turn the practice of medicine into a science.
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David McCandless: The beauty of data visualization | Video on TED.com

TED Talks David McCandless turns complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out unseen patterns and connections.
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Universities back venture capital fund - Entrepreneur News | Australian Society of Entrepreneurs

Universities back venture capital fund - Entrepreneur News | Australian Society of Entrepreneurs | Big Data Venture Capital | Scoop.it
Rock Spring Ventures has gathered an unusual pooled commitment of £6m from the endowments of Aberdeen, Glasgow and Edinburgh universities Financial Times - Entrepreneurship ...
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