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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.

 

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cố định và bảo vệ hàng hóa tốt hơn trong quá trình vận chuyển tránh
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Chọn loại pallet nhựa tiêu chuẩn

Các sản phẩm pallet nhựa đạt tiêu chuẩn thường được thiết kế dạng đế chữ nhật với kích thước đa dạng
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làm lót sàn kho nông sản, đông lạnh, sàn bếp ăn công nghiệp,…

sử dụng giản đơn, không xảy ra mối mọt,
cong vênh

Các loại pallet cần phải có tính ứng dụng cao,
khả năng tận dụng trong nhiều điều
kiện môi trường khác biệt. Đối với những môi trường như
nước, hóa chất, ẩm ướt pallet không chịu bất cứ tác động nào.


Chiều cao hợp lí

Tùy vào yêu cầu như dự tính sử dụng để chọn loại pallet có chiều cao hợp
lí. Nếu bạn sử dụng cho hàng đóng gói nông sản, dược phẩm nên chọn loại có độ cao 10,
12, 13cm để đảm bảo tiêu chí kỹ thuật và giá cả phải chăng.


Mục đích sử dụng. http://sco.lt/6pjVs8


Dựa vào mục đích dùng để chọn loại pallet phù hợp

Nếu bạn đang muốn sử dụng pallet để kê
hàng hóa hay vận chuyển, luân chuyển hàng hóa một cách nhanh chóng thì nên chọn loại pallet cũ giá rẻ đã từng sử dụng qua một lần. sản phẩm
này tính năng giúp bạn tiết kiệm được tối đa chi phí so với việc mua các sản phẩm có mức giá cao.


Địa chỉ cung cấp pallet nhựa hạ giá TPHCM uy tín, chất lượng

Hiện nay tại khu vực TP. Hồ Chí Minh có số
đông cơ sở cung cấp pallet nhựa giá rẻ.
Ngược laị, sự đặc biệt về chất lượng
và tầm giá ở mỗi Địa chỉ rất lớn. Điều này khiến việc tuyển lựa một
nhà cung cấp đảm bảo uy tín, chất lượng của khách hàng càng khó khăn hơn.



Mai Lợi cơ sở cung cấp các cống phẩm pallet nhựa
rẻ đảm bảo chất lượng

Công ty TNHH SX TM DV Mai Lợi là một trong những doanh nghiệp được khách
hàng đánh giá rất cao về những ưu điểm nổi bật trong chương trình phân phối pallet nhựa giá rẻ thành phố hồ chí
minh như:

Các vật phẩm đảm bảo độ bền cao, tính năng chống chịu
tốt.
tầm giá vật phẩm phải chăng, tiết kiệm tối đa chi phí cho khách hàng.

Nhiều chương trình khuyến mãi với các ưu đãi thu hút
bắt đầu thường xuyên.
Các vật phẩm pallet đa dạng mang lại nhiều sự sàng lọc cho người chi tiêu.


Nếu bạn có nguồn tài chính eo hẹp hay chỉ sử dụng trong
một thời khắc nhất định, bạn có thể cân nhắc các
vật phẩm pallet nhựa cũ giá rẻ TPHCM để tiết kiệm chi phí tối đa.

khoảng thời gian vận chuyển sản phẩm nhanh chóng,
đảm bảo giao hàng đúng tiến độ đã cam kết.

Trên đây là Một số chia sẻ về cách
tuyển chọn pallet nhựa giá thấp nhất đảm bảo chất lượng trong
quá trình dùng. Hãy liên hệ ngay với chúng tôi nếu bạn đang có làm theo
đặt hàng sản phẩm với độ bền vượt trội này nhé.
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