ETL Guide 2022 from “Into The Minds”: Anatella dominates the market
Whatever the criteria used to qualify an ETL (scope of functionality, speed of execution, quality of customer support, etc.), the dominant ETL…
Blog
News, product updates and technical articles from the TIMi team.
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The 11 challenges of data preparation and data wrangling
The events of 2020 have accelerated the shift to teleworking and digital relationships. With digitalisation, another transformation is also underway: the analytical…
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What’s the best machine for data science?
What’s the best machine for data science? A recurrent question in many data science blogs is “hey guys, what machine would your…
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The place of data wrangling in the data value cycle
Learn more about data wrangling and how we position it within the data value cycle.
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Why we fail with machine learning, and how to avoid it.
With 53-90 of project failure, chances are each of us will be confronted to it. If making mistakes is part of the…
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Stop obsessing about a perfect model
A perfect model is often an illusion because of the ratio effort / impact, Model Quality Decay and Prediction Window. To be…
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Let’s stop misleading our users with meaningless classification rates!
So, you think AI classifies well? How we end up misleading AI users about the efficiency of classification models
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Data wrangling: definition, steps, tools
Data scientists spend a large portion of their time on data preparation activities. Much of this data preparation activity involves data wrangling.
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Data preparation: definition, examples, advices
Discover the most frequently encountered problems, tools, and trends for data preparation.
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