4 Technological Solutions to Improve Data Quality for AI Initiatives

By Petr Nemeth | 1 min read

In discussions about AI tools and workloads, the emphasis tends to be on optimizing machine learning models, rather than ensuring they are fed high-quality data. But, if garbage in means garbage out, then keeping data quality high is just as important as building and training the models.

In a guest article for Solutions Review, Dataddo CEO Petr Nemeth discusses four categories of tooling that can help businesses achieve AI-friendly data quality, with takeaways for each category:

  • Data integration
  • Data profiling and filtering
  • Data labelling
  • Data monitoring and lineage

Read the full article at solutionsreview.com.



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Category: Tools, Industry Insights, data-strategy