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The Lab's missions

DQ

Our challenge is to demystify data quality issues, which are often considered tedious, thanks to simple AI-powered tools that can be used directly by the Business teams.

  • Write publications around exploratory data quality topics,
  • Develop solutions to make them available to Heka.ai Data Scientists,
  • Offer an internal and external expertise service on the subject.

Our AI solutions for Data Quality

Our publications

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Synthetic data or how to share sensitive data…

For a period of six months, 5 students from Centrale Supélec and ESSEC worked collaboratively with Sia Partners on building a Python library to create fake - which we'll call synthetic - data.
But what's the point of creating fake data? How could it help organizations?

2023

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Introduction to OpenStreetMap: How to leverage…

In this article, we explore the use of OpenStreetMap for extracting geospatial data and implementing an approach to enhance the overall data quality. We delve into the key steps of data extraction including selecting the area of interest, data collection, cleaning, and preparing data for future use.

2023

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Customer churn prediction with Data Science

Thanks to Machine Learning, companies can significantly improve their activities by leveraging their data. Machine Learning is a field of study of artificial intelligence that gives an AI the ability to "learn" from data.

2023

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