As artificial intelligence (AI) shapes the future of business, data quality is emerging as the essential pillar of success.
Michel Savard, Data Science Practice Leader at CRIM, rightly points out: “What’s unique to a company is its data. That’s where the return on investment lies.
According to Varibase’s Digital Marketing Survey 2023, although 55% of Quebec companies have data management platforms, their maturity remains moderate, rated at 3.2 out of 10. The question is: How can you ensure the success of your shift to artificial intelligence while minimizing the potential risks?
That’s when CRIM’s experts come into play for a successful digital transformation and guarantee the success of AI projects . The article published by Les Affaires highlights the main lines addressed by CRIM to ensure data quality:
1. The challenge of misunderstood data :
CRIM’s NUMERIA program offers essential support to SMEs, helping them to de-risk their AI projects.
2. Data quality for effective predictive models :
Beyond quantity, CRIM insists on the importance of data quality for effective predictive models.
3. Going beyond raw data :
Data governance becomes essential to guarantee the reliability and relevance of the information used.
4. In search of the “ground truth” :
Information that is often overlooked can prove crucial to the success of an AI project.
5. Invest in data quality :
The key to success in AI lies in continuous investment in data quality.
Read Michelle Savard’s full interview “The art of annotating your data”, published in Les Affaires.