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Data Visualization #Design by Etan Lightstone at FutureStack13 | #dataviz #workflow

luiy's insight:

Data visualizations have become a first class citizen of information dissemination on the web, and a powerful tool when used effectively in product user interfaces . With technologies like D3, we are able to provide a great deal of interactivity to these visualizations, and with almost unlimited possibilities. This talk will be focusing on how to design effective data visualizations:

* Design process for data viz
* Visual design patterns to follow
* Using the right charts
* Data mining, and cutting through the noise of very large data sets

 

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Data Vis Consulting: Advice for Newbies I #dataviz #workflow - @moritz_stefaner

Data Vis Consulting: Advice for Newbies I #dataviz #workflow - @moritz_stefaner | e-Xploration | Scoop.it
luiy's insight:

Moritz, who most frequently works on what I'd class as "cool data set vis" projects, tells me he usually requests a data sample and some answers to a few questionsclarifying the context and basic motivation of the project before starting:

 

Why are we doing this?What are you hoping to achieve?Who are we targeting?How is the end product going to be used?How are we publishing?What data do we have available?Which other existing materials should we take into account?Which constraints do we have?Who is responsible for what?Who else is doing something similar?

 

For Moritz, answers to these questions help him understand why the client thinks a data visualization is important, and also help define success criteria for the project. He says, “Often, both the client and I realize that half of these questions cannot be answered yet, but that's fine, as long as we make sure to answer them along the way.” 

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Data Perspective: Data Analysis Steps | #datascience #workflow

Data Perspective: Data Analysis Steps | #datascience #workflow | e-Xploration | Scoop.it
data analysis steps, how to implement data analysis, how to solve data analysis problem
luiy's insight:

After going through the overview of tools & technologies needed to become a Data scientist in my previous blog post, in this post, we shall understand how to tackle a data analysis problem. Any data analysis project starts with identifying a business problem where historical data exists. A business problem can be anything which can include prediction problems, analyzing customer behavior, identifying new patterns from past events, building recommendation engines etc.

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