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How Can Thick Data Improve the Way We Use Big Data?

Troy Sadkowsky - Friday, June 30, 2017

 

April 16, 2017

TedTalk: https://www.youtube.com/watch?v=WaOUJa9fjXU

Medium: https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7

Big data can help us solve problems, optimize services, predict the future and learn more about ourselves and human behavior. But when big data cannot answer a question, or makes an incorrect prediction, what if it is because data is not telling us the whole story?

In a Ted Talk and an article on Medium, Tricia Wang, a technology ethnographer, implores us to realize that, even in the age of data-driven decision making, big data can have some serious blind spots, and often suffers from a loss of context through valuable variables and trends that defy quantification.

Insights on contained systems, such as electricity grids or delivery logistics, have established big data’s reputation for success. Although this reputation has attracted investment from a huge array of companies, Wang claims, 73% of big data projects are not profitable, because big data projects frequently do not produce the insights that they seem to promise. For dynamic systems, especially those that depend on human emotions, behavior, and how people are impacted and interact with their environment, certain variables are difficult to measure and model.

She describes how opportunities can be gained and losses diminished by using big data in conjugation with “thick data”, observations that use qualitative methods to understand human emotions, behaviors and interactions with context. For example, the realization by ethnographer Graham McCracken that Netflix users actually enjoy binge-watching, led Netflix to redesign their user experience, improve their business and transform the way we consume media. Through qualitative research and collecting stories about how users interact with their product, Netflix was able to go to their data science team, validate these findings, and act on this competitive insight.

Wang summarizes that while “Thick Data loses scale…Big Data loses resolution.” While big data analytics can have a huge sample size, recognize large-scale patterns, and benefit from the strengths of machine learning, thick data uses small samples sizes, but understands subjects at a much greater depth, and benefits from aspects of human intelligence and pattern recognition that still elude computer programs. As data scientists, the more we understand the limitations of our methods and pay attention to thick data, the more we can recognize the factors and variables our data is missing. With a more holistic perspective, data analysis is better poised to uncover more truthful and powerful insights.

 

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How Can Thick Data Improve the Way We Use Big Data?

Troy Sadkowsky - Friday, June 30, 2017

 

April 16, 2017

TedTalk: https://www.youtube.com/watch?v=WaOUJa9fjXU

Medium: https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7

Big data can help us solve problems, optimize services, predict the future and learn more about ourselves and human behavior. But when big data cannot answer a question, or makes an incorrect prediction, what if it is because data is not telling us the whole story?

In a Ted Talk and an article on Medium, Tricia Wang, a technology ethnographer, implores us to realize that, even in the age of data-driven decision making, big data can have some serious blind spots, and often suffers from a loss of context through valuable variables and trends that defy quantification.

Insights on contained systems, such as electricity grids or delivery logistics, have established big data’s reputation for success. Although this reputation has attracted investment from a huge array of companies, Wang claims, 73% of big data projects are not profitable, because big data projects frequently do not produce the insights that they seem to promise. For dynamic systems, especially those that depend on human emotions, behavior, and how people are impacted and interact with their environment, certain variables are difficult to measure and model.

She describes how opportunities can be gained and losses diminished by using big data in conjugation with “thick data”, observations that use qualitative methods to understand human emotions, behaviors and interactions with context. For example, the realization by ethnographer Graham McCracken that Netflix users actually enjoy binge-watching, led Netflix to redesign their user experience, improve their business and transform the way we consume media. Through qualitative research and collecting stories about how users interact with their product, Netflix was able to go to their data science team, validate these findings, and act on this competitive insight.

Wang summarizes that while “Thick Data loses scale…Big Data loses resolution.” While big data analytics can have a huge sample size, recognize large-scale patterns, and benefit from the strengths of machine learning, thick data uses small samples sizes, but understands subjects at a much greater depth, and benefits from aspects of human intelligence and pattern recognition that still elude computer programs. As data scientists, the more we understand the limitations of our methods and pay attention to thick data, the more we can recognize the factors and variables our data is missing. With a more holistic perspective, data analysis is better poised to uncover more truthful and powerful insights.

 

Comments
rose garden commented on 06-Dec-2018 11:23 PM
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site is providing.
Hayden commented on 06-Dec-2018 11:26 PM
I'm really enjoying the design and layout of your site. It's a very easy on the eyes which makes it much more enjoyable for me to come here and visit more often. Did you hire out a developer to create your theme?
Exceptional work!

Check out my web site; Www.Real.G6.Cz
Annabelle commented on 06-Dec-2018 11:47 PM
Good day! This is my first visit to your blog!

We are a team of volunteers and starting a new initiative in a community
in the same niche. Your blog provided us valuable information to work on. You have done a marvellous
job!
http://Oedaundrea0748599.wikidot.com/Blog:51 commented on 07-Dec-2018 12:07 AM
Hi, of course this post is in fact pleasant and I have learned lot of things from it on the topic of
blogging. thanks.
Computer Ebook Download In Hindi commented on 07-Dec-2018 12:29 AM
It's appropriate time to make some plans for
the future and it is time to be happy. I've read this post and if I could I want
to suggest you some interesting things or advice.
Maybe you could write next articles referring to this article.
I wish to read even more things about it!
Concetta commented on 07-Dec-2018 12:51 AM
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blogger sites For insomniacs commented on 07-Dec-2018 01:03 AM
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who are not afraid to say how they believe.

At all times follow your heart.
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Why viewers still use to read news papers when in this
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188 commented on 07-Dec-2018 01:27 AM
If you happen to be travelling to another city and find that there's a good show in this city,
you can't look at different companies for your box office, stand it a line and get the tickets.
"Because you happen to be here looking over this online games report now with this particular moment in time; what you have is "The first movers advantage" yourself to adopt a hold of now. The plastic's name can often be abbreviated to CR-39, standing for Columbia Resin, and it's also less than 50 % the body weight of glass, which supplanted quartz inside early twentieth century.
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born inside the Florentine Republic on April 15th, 1452.
Matisse also became the king from the Fauvism and was famous within the art circle.
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It is common to find the ornamental painting and sculptures with shapes
depicting an appealing mixture of different components from the artist's
religious, physical and cultural background. If this is
a matter of yours too, then you should learn concerning the best ways
to procure such things. The beginning of Leonardo's life was dedicated to art and painting
in particular.
pdf download adobe For Mac commented on 07-Dec-2018 08:54 AM
With havin so much written content do you ever run into
any issues of plagorism or copyright violation? My blog has a lot of exclusive content I've either written myself or outsourced but it seems a lot of it is popping it up all over the web without my
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Vishal Saree Australia - Sudarshansilk.com commented on 07-Dec-2018 11:25 AM
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Thank you for sharing!

Post a Comment




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Trackback Link
http://www.datascientists.net/BlogRetrieve.aspx?BlogID=10882&PostID=712403&A=Trackback
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