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Go Clean to Be Lean: Data Optimization for Improved Business Efficiency
Manage episode 424956039 series 3474670
This story was originally published on HackerNoon at: https://hackernoon.com/go-clean-to-be-lean-data-optimization-for-improved-business-efficiency.
The article discusses cost optimization with clean data, explaining how businesses can save resources by reducing the workload for data analysts and more.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-cleaning, #data-optimization, #data-cleansing, #clean-data, #big-data, #big-data-processing, #data-processing, #business-data, and more.
This story was written by: @karolisdidziulis. Learn more about this writer by checking @karolisdidziulis's about page, and for more stories, please visit hackernoon.com.
This article discusses cost optimization with clean data. It explains how businesses can save resources by decreasing the load for data analysts, among other opportunities. It also discusses the differences between raw and clean data and who can benefit from switching to the latter. You'll also find 4 ways in which clean data reduces time to value.
126 afleveringen
Manage episode 424956039 series 3474670
This story was originally published on HackerNoon at: https://hackernoon.com/go-clean-to-be-lean-data-optimization-for-improved-business-efficiency.
The article discusses cost optimization with clean data, explaining how businesses can save resources by reducing the workload for data analysts and more.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-cleaning, #data-optimization, #data-cleansing, #clean-data, #big-data, #big-data-processing, #data-processing, #business-data, and more.
This story was written by: @karolisdidziulis. Learn more about this writer by checking @karolisdidziulis's about page, and for more stories, please visit hackernoon.com.
This article discusses cost optimization with clean data. It explains how businesses can save resources by decreasing the load for data analysts, among other opportunities. It also discusses the differences between raw and clean data and who can benefit from switching to the latter. You'll also find 4 ways in which clean data reduces time to value.
126 afleveringen
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