The Volume, Velocity, Variety, and Visualization of Big Data

What if We had More Big Data Artists in the World?

Today’s Big Data Scientists are being challenged with discovering actionable insights from the Volume, Velocity and Variety of data resources in cost-effective innovate ways. This is the foundation of Big Data Trends and has tremendous value when understanding is Visualized by today’s Big Data Artists.

Big Data Artists and Data Storytelling

Data comes to life in the hands of Data Artists.  Effective Data Storytelling can inspire new ideas and actions. Statistics guru Hans Rosling is a modern day Michelangelo of Big Data.  Watch his TED Talk video about “global trends in health and economics“.  Hans really gets rolling into this data story at about the 4 minute mark of this video.

Big Data Virtualization

Processing unstructured, semi-structured, and structured data can be accomplished with open-source tools such as Hadoop, MongoDB, Node.JS, with multiple programming languages including Java and Python. Many of these Big Data Tools can be installed and configured within a few minutes.  We can also leverage Cloud Computing for processing Big Data. Cost-effective processing of Graph Data for Social Network Analytics can be accomplished with GraphChi.  My friend and colleague, Brad Cox, created an easy to use plugin to accelerate graph data processing.  There are a plethora of tools and resources out there.  Help others and share your favorites here.

Big Data Visualization

Getting the right information to the right person at the right time in the right way is a big deal.  Data Visualizations should not be cryptic like a puzzle, but easy to understand.  This is not a simple task and is the reason why we need more Big Data Artists in the world. My friend Angela Dunn has inspiring Data Visualization stories at Data is Beautiful.

Data Visualization Tools

Great artists experiment with a variety of material and tools to create their masterpieces.  The modern day Big Data Artist can experiment with these tools to create their next masterpiece.

Gephi The Open Graph Viz Platform: Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs.  This tool makes it fun to experiment with GraphData.

RapidMiner Data Mining System: RapidMiner is an open-source system for data mining. It is available as a stand-alone application for data analysis and as a data mining engine for the integration into custom products.

Sencha Ext JS is an “Enterprise grade JavaScript Framework”.  Ext JS Plugin-free Charting provides advanced charting and graphing capabilities, delivering pixel perfect visuals on any browser on any operating system.

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

Highcharts is a charting library written in pure JavaScript, offering intuitive, interactive charts to your web site or web application. Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange and polar chart types.

Raphaël is a small JavaScript library that should simplify your work with vector graphics.  Raphaël ['ræfeɪəl] uses the SVG W3C Recommendation and VML as a base for creating graphics. This means every graphical object you create is also a DOM object, so you can attach JavaScript event handlers or modify them later. Raphaël’s goal is to provide an adapter that will make drawing vector art compatible cross-browser and easy.

Visual.ly supports Visual Storytelling with data visualizations and infographics.     Visually’s Visual Reports can turn monthly performance metrics into a powerful visual narrative that communicates company objectives and milestones to both internal and external stakeholders. Infographics can also communicate product features.

Visualizing data helps others understand the value of information.  Additional data visualization tools are available here Top 20 Data Visualization Tools.  Visual content inspires conversation, as I was writing this, my friend Kathy Meyer shared this article about using visual content to inspire conversation 26 Ways to Use Visuals in Your Social Media Marketing

Big Data & Visualization Resources

Learning more about Big Data and the art of data visualization is a valuable skill to master.  There are several online classes and meetups in the area.  A recent meetup in the Washington DC area was Uncovering Hidden Social Information with Prof. Jennifer Golbeck. Her book, “Analyzing the Social Web” is available on Amazon.  Another great book to help you master the art of Big Data and Social Network Analytics is, “Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites”.

Summary

Big Data is the Gold Rush of the 21st Century where discovering nuggets of actionable insights is transforming the way we work, live, & play.  Big Data Is Changing the Whole Equation for Business and organizations that fail to define Big Data Leadership will fall behind, far behind.  Organizations that hope to remain competitive in today’s market will include a strategy that implements Big Data tools along with the training and development of Data Scientists and Big Data Artists.

6 thoughts on “The Volume, Velocity, Variety, and Visualization of Big Data

  1. Pingback: The Volume, Velocity, Variety, and Visualization of Big Data | Data is Beautiful | Scoop.it

  2. Pingback: The 4 Vs of Big Data | e-Xploration | Scoop.it

  3. Pingback: What if we had more big data artists in the world ? | Datagraphie des flux d'information & Solidarités | Scoop.it

  4. This post is very inspiring! I think the potential of big data is vast but it is just slowly being realized. I’ve been working in gamification for about 10 years (before the term was coined), but earlier there weren’t enough mechanisms to collect and understand data to truly utilize the full potential of gamification (even today). Obviously everything is tracked in a game, but in the real world, when you require people to manually enter any data, it creates mass friction.

    I think with better big data talent and technologies, gamification becomes a much more powerful application of the data that is utilized (using the data to motivate and engage people to do things).

    I recently also published a complete gamification framework called Octalysis (http://bit.ly/octalysis) and it took off – being translated into 7 different languages, and I think it will be something very useful in fueling the big data-gamification revolution. Check it out.

    Again, thanks so much for this great post. Keep up the good stuff!

  5. Pingback: The 4 Vs of Big Data | Big Data | Scoop.it

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