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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
mezo commented on 29-Mar-2018 09:18 AM
І couⅼdn't refrain frolm commenting. Perfectly ѡritten!
Paul Loves Honeywell Wireless Alarm Systems commented on 04-Apr-2018 10:53 PM
I've been exploring this area for around three weeks at this point and this really is the 1st page that absolutely makes sense. How come it's so hard to gather effective specifics relating to security these days? Surely value the time you invested getting your concepts in to words so novices just like me can certainly take action. Will there be a part two on your blog post? Many thanks!
Link 188Bet commented on 05-Apr-2018 02:05 AM
The camera may make the brightest of scenes appear to be it was taken during an eclipse.
A model with 3 CCD features a sensor that sees each of the different colors (Red, Green,
and Blue) leading to superior color reproduction. You need a special connector typically termed as a Fire wire
or sometimes known being an IEEE 1394 high band connector.
mattel superhero dolls commented on 05-Apr-2018 05:33 PM
I was recommended this blog by means of my cousin. I am no longer positive
whether or not this publish is written by him as nobody else realize such unique approximately my difficulty.

You are wonderful! Thanks!
superhero toys for 6 year old commented on 08-Apr-2018 12:52 PM
This is really interesting, You are a very skilled blogger.
I've joined your feed and look forward to seeking more
of your magnificent post. Also, I've shared your site in my social networks!
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Too many cooks commented on 16-Apr-2018 03:23 PM
These two better settle their score now before everything ends up burnt!
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These two better settle their score now before everything ends up burnt!
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it to load properly. I had been wondering if your hosting is OK?
Not that I am complaining, but slow loading instances times will often affect
your placement in google and could damage your quality score if advertising and marketing
with Adwords. Well I am adding this RSS to my e-mail and could look out for
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you update this again very soon.
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