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Synthetic Data
Why and when to use it?
Why Synthetic Data?
One of the biggest challenges working with data is related to Data Quality. In several aspects.
According to O’Reilly’s research, AI adoption in the Enterprise 2022, only 26% of the companies have their AI projects in production.
So, AI projects are not being as successful as expected.
Bottlenecks
We asked respondents what the biggest bottlenecks were to AI adoption. The answers were strikingly similar to last year’s. Taken together, respondents with AI in production and respondents who were evaluating AI say the biggest bottlenecks were lack of skilled people and lack of data or data quality issues (both at 20%), followed by finding appropriate use cases (16%).
According to the survey the main bottlenecks are:
Lack of skilled people AND data OR data quality (40%)
You can see the full survey results using the link below:
