Contemporary Analysis

Data Science

Tadd Wood

The Predictive Analytics Revolution - Are you sitting on the sidelines?

Predictive analytics (or Big Data) is here to stay. You may not understand it. You may not believe that it really works. But the reality is this: your competitors (and it may be just one or two of them) are using predictive analytics to chew up market space as you remain on the sidelines.

Don’t believe me?

Grant Stanley

Why Visualizing Data is Important

Visualizing data can make something easier to understand and perhaps keep you awake.  Most students have learned that the cure for insomnia is take a difficult concept, like the philosophical concept of determinism, and explain it with words alone. In case you don’t know, Determinism is defined as “events within a given paradigm are bound by causality in such a way that any state of an object or event is determined by prior states.” Asleep yet? But what if you explain that concept with a picture?

Notice how the explanation become more interesting and relevant with a visual aid? I’m sure you had the same reaction as me. Even though I might not care what determinism means, the picture piqued my curiosity and drew me in to explore the topic than I would have otherwise. The illustration makes a hard concept easy to grasp. Download our eBook, "Dashboards: Take a closer look at your data".

Visualizing a concept has an amazing affect on the human mind.

Tadd Wood

A Preattentive Dashboard

The visual world is extraordinarily complex.  For example a quick scan of my desk reveals hand-written notes, dry erase markers and USB thumb-drive.  While I recognize these objects rapidly, I experience them at a basic visual perceptual level long before I can label or describe them.  This low level of perception is what is called preattentive processing, or visual processing that occurs without deliberate attention.  Preattentive processing can be used to create dashboards that easily communicate extraordinary amount of information per pixel and need very little effort to understand. Download our eBook, "Dashboards: Take a closer look at your data".

Tadd Wood

Using Tableau Reference Lines to Explore Data

At CAN, as needed we use the visualization software Tableau to create reports and dashboards for our clients.   Also, because Tableau is capable of handling large amounts of data very quickly, we’ve started using it to explore data visually during the data discovery stage of each project.  We use Tableau to check the quality of data, find outliers, and get a sense of the properties of a data set, such as dispersion, central tendency, clustering, etc., before we apply statistical analysis or build predictive models.  A Tableau feature, especially useful for exploring data, are Reference Lines.

This blog post explains a few ways that CAN uses Tableau to explore a data set.


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