The document discusses emerging trends in business intelligence presented by Bijilash Babu on July 20, 2012, focusing on big data, its visualization, and the importance of using advanced technologies for better data analysis and decision-making. It highlights various data visualization techniques, the exponential growth of data, and the necessity for effective methods to extract relevant insights. Mathematical methods, such as classification and regression, are emphasized to support analysis amidst increasing data complexities.

1. Advanced Visualization
Bijilash Babu
Technical Architect
Technology Development Centre
NeST Software
bijilash.babu@nestgroup.net
Session on Emerging trends in
Business Intelligence
20 July 2012: Zenith Hall
Bhavani, Technopark, Trivandrum

2. Roadmap
• Big Data
• Dimensionality
• Current trends
• Ordinary analytics
• Applied mathematics
• Advanced Technology
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3. Big Data, It’s Visualization
• Gartner’s definition of big data refers to high-volume, high-velocity and high-
variety information assets that demand cost-effective, innovative forms of
information processing for enhanced insight and decision making.
• Big Data is the convergence of three v’s: volume, velocity and variety .
• Internet of things (with different sensors), CRM, social media, etc..
• Improved use of Big Data could add X to the economy and create N jobs.
• Volume of data keeps creeping, Decision makers would struggle..
• Data visualisation is the key for better perception of the underlying facts.
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4. When big wasn’t that big
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• Line graph
• Stack graph
• Categories Stack graph
Track rises and falls over time
• Scatterplot
• Matrix chart
• Network Diagram
See relationships among data points
• Bar chart
• Block histogram
• Bubble chart
Compare a set of values
• Pie Chart
• Tree Map
• Analyze a text
• Word tree
• Wordle
See parts of a whole
• Mapping
See the world

5. Better Representation
9876546765 987-654-6765
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Source: www.cia.gov

6. Timeline
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Source: The Economist

7. Better Representation
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Source: The New York Times

8. The volcano
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9. Create your own visual
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Source: www.wordle.net
George K. Thiruvathukal,
Associate Editor in Chief
Computing in Science & Engineering
Tag Cloud, NSF proposals

10. Create your own visual
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Created in R with word-cloud package. Data from country population. Note that the proportional sizes of China
and India were reduced in half. Source: wikipedia.org

11. What’s up..
• Need to bring in better methods for extracting a smaller
set of relevant data.
• In fact, Big Data isn’t just about numbers or volume, but
the trends – how they change over time.
• Visualization is an invaluable tool in identifying trends
within massive data sets.
• Spotting anomalies as well as outliers.
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12. Going around Big Data
• With the exponential growth in data acquisition and
generation.
• High-resolution sensors, automated accumulation...
• More disk space and more CPU cycles!
• But, there are couple of walls around the CPU,
• and GPUs come into picture!
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13. Calling in Maths
• Scientific data analysis techniques
• Numerical Linear Algebra
• SVD - The prize, compression
• PCA/ NLPCA – to reduce the dimensionality, feature extraction
Latent Semantic Indexing (LSI)
• SVM - classification, regression, and anomaly detection.
• SOM - neural network algorithm based on unsupervised learning
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14. Log plots
• Response to skewness towards large values; i.e., cases in which one or a
few points are much larger than the bulk of the data.
• To show percent change or multiplicative factors.
• Base of ten is useful when the data range over several orders of magnitude,
a base of two is useful when the data have a smaller range
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Source: Forbes

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16. Better Mixing
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+ = ?

17. Visual data Mining
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Source: S.J. Simoff et al. (Eds.): Visual Data Mining, LNCS 4404

18. Advanced technology
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19. Hans Rosling...
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...What’s next?

20. Thank you!!!
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