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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
National Security News commented on 18-Sep-2018 05:53 AM
If some one desires expert view about blogging and site-building
after that i recommend him/her to pay a visit this blog,
Keep up the pleasant job.
Aimee commented on 18-Sep-2018 05:56 AM
Fortunately, there are ways to make experience easier for the online shopper.
This has increased its efficiency jointly interested with a
part of any type of vehicle will surely get it off their company.

User OEM Parts - Used car parts are generally staked in a used garage or a junk
shop.
Michell commented on 18-Sep-2018 06:01 AM
A domain is merely among those names.
Amie commented on 18-Sep-2018 06:02 AM
Every day,countless domain names are signed up.
california Divorce process commented on 18-Sep-2018 06:08 AM
Your method of explaining all in this article is genuinely nice, all be capable of simply know it,
Thanks a lot.
Jetta commented on 18-Sep-2018 06:14 AM
I love the information on your websites. Thank you so much.



Feel free to surf to my web site:types of accessories
Almeda commented on 18-Sep-2018 07:32 AM
Short domain names are better than long domain names.
Terrie commented on 18-Sep-2018 07:57 AM
I visited several blogs except the audio feature for audio songs existing at this web page is really excellent.


Also visit my homepageDivorce Corp
Amee commented on 18-Sep-2018 08:40 AM
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enhance SEO.
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a hyperlink change contract among us
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I have cherished the Air Max footwear and have run damage free till final month, after I
tore my TFL.
kobe shoes commented on 18-Sep-2018 09:41 AM
A right pair of basketball sneakers undeniably will
make it easier to make an excellent performance on the court by preserving your ft in correct
balance and alignment.
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Turnes Air cushion was a hemisphere-form cushioning system which
may provide a most pressure protection, stable and comfort foot feeling,
essentially the most eye-catching place was that its variable hemisphere-form shoe body can altering the air
pressure in response to its demand.
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sportswear corporations.
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$200 million deal with Adidas however he's already crossing some major strains!
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The American Council on Exercise stories that the outsole protection offered by the
sneakers reduces damage to the feet.
kobe shoes commented on 18-Sep-2018 11:01 AM
NBA celebrity Charles Barkley was the primary African-American to endorse the
sneakers.
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