Blog | Intelligence des données | Juillet 3, 2018 | 1 min de lecture

Data Mapping: The Challenges in an Organization

By Actian Corporation

#Big Data gouvernance des données gouvernance #Qualité des données #Data scientist
modernisation des données

By Actian Corporation

#Big Data gouvernance des données gouvernance #Qualité des données #Data scientist

Summary

  • Le Big Data accroît la complexité de découverte de données, de leur utilisation et de gouvernance.
  • Les entreprises ont du mal à cerner les sources de données, les transformations et les répercussions.
  • Les questions clés portent sur la pertinence, la sensibilité, l'origine et les répercussions.
  • La traçabilité des données améliore la qualité des données, la conformité (par exemple, au RGPD) et la transparence.
  • Permet aux utilisateurs de mieux comprendre, de faire confiance aux données et de les utiliser de manière autonome.

The arrival of Big Data did not simplify how enterprises work with data. The volume, the variety, and the various data storage systems are exploding. With the Big Data revolution, it is even more difficult to answer “primary” questions related to data mapping:

  • What are the most pertinent datasets and tables for my use cases and my organization?
  • Do I have sensitive data? How are they used?
  • Where does my data come from? How have they been transformed?
  • What will be the impacts on my datasets if they are transformed?

So many questions that information systems managers, Data Lab managers, Data Analysts, or even Data Scientists ask themselves to be able to deliver efficient and pertinent data analysis.

Among others, these questions allow enterprises to:

  • Improve data quality: Providing as much information as possible allows users to know if the data is suitable for use.
  • Comply with European regulations (GDPR): mark personal data and the carried-out processes.
  • Make employees more efficient and autonomous in understanding data through graphical and ergonomic data mapping.

To put these into action, companies must build what is called data lineage.