Why Data Science Projects Fail

Balaram Panda
8/8/2023
cs.LGcs.CYcs.DB

No official code found. Best implementation: xLaszlo/datascience-fails (462 stars, MIT, last commit 2021-03-14).

Abstract

Data Science is a modern Data Intelligence practice, which is the core of many businesses and helps businesses build smart strategies around to deal with businesses challenges more efficiently. Data Science practice also helps in automating business processes using the algorithm, and it has several other benefits, which also deliver in a non-profitable framework. In regards to data science, three key components primarily influence the effective outcome of a data science project. Those are 1.Availability of Data 2.Algorithm 3.Processing power or infrastructure

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Code Implementations(1)

xLaszlo/datascience-failsCommunity67%
MIT

Collection of articles listing reasons why data science projects fail.

46221Aug 30, 20205 years agoMIT

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Cite this paper

@article{panda2023data,
  title  = {Why Data Science Projects Fail},
  author = {Balaram Panda},
  year   = {2023},
  eprint = {2308.04896},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.04896v1}
}

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