Remove 2013 Remove IT Remove Visualization
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7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++

Occam's Razor

Ditch the text, visualize the story. Advanced, sophisticated visualizations are important. Hence all the insights-free data visualizations floating around the web that are totally value-deficient, even as they are pretty. Then, go express your inner visualization beast. :). [My All well and good. The last mile.

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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

In 2013, less than 0.5% We gave you a curated list of our top 15 data analytics books , top 18 data visualization books , top 16 SQL books – and, as promised, we’re going to tell you all about the world’s best books on data science. Why You Need To Read Data Science Books. of all available data was analyzed, used, and understood.

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Why Game Studios Should Exploit Visual Analytics | BizAcuity

BizAcuity

GAMWIT , a SaaS solution built by BizAcuity empowers game developers with powerful visual analytics. Evolution from MS Excel to Visual Reporting. Integrated data capture and visual analytics is not possible with Excel. Modern Visual Analytics Tools. Introduction. Inability to get player level data from the operators.

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Data Visualizations in Python and R

Sisense

The human brain processes visual data better than any other kind of data, which is good because about 90% of the information our brains process is visual. Visual processing and responses both occur more quickly compared to other stimuli. The brain processes data in visuals or images faster than data in text or rows of numbers.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? But today, dashboards and visualizations have become table stakes. Five years ago they may have. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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From Disparate Data to Visualized Knowledge Part III: The Outsider Perspective

Ontotext

In 2013, actually, with SPARQL 1.1. In our previous blog posts of the series, we talked about how to ingest data from different sources into GraphDB , validate it and infer new knowledge from the extant facts as well as how to adapt and scale our basic solution. So, let’s see what can be done here. SPARQL federation.

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Academic Research Done on Arc Diagrams

The Data Visualisation Catalogue

Arc Diagrams: Visualizing Structure in Strings (2002) By Martin Wattenberg Topic: Data Visualisation. Thread Arcs: an email thread visualization (2003) By Bernard Kerr Topic: Data Visualisation. R-CHIE : a web server and R package for visualizing RNA secondary structures (2012) By Daniel Lai, Jeff R. Wiebe and Irmtraud M.