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If your small business is still in its early stages, it’s likely that synthetic data generation hasn’t entered your head yet. Even if you’ve been operating for a few years, you might not yet realise how crucial realistic and compliant synthetic data can be for your operations, and that’s understandable.
Over the last few years, a lot has been said of its importance for big businesses – enterprises that handle massive volumes of sensitive data and operate under strict regulatory requirements. But as we move closer to a more AI-driven, data-intensive future, it’s important that every business gets involved, ensuring that development, testing, and AI initiatives are safe and accurate from the start.
So what are the best synthetic data generation tools for small businesses, specifically? We’re going to look at the top 7 below, explaining a bit about what they do and why they should be your next consideration.
- K2view
For companies requiring a comprehensive solution for managing the entire synthetic data lifecycle, including source data extraction, subsetting, pipelining, and synthetic test data operations, K2view is probably your best bet. With GenAI and rules-based data generation methods and patented technology that maintains data integrity – this is a full-featured standalone solution that delivers the best bang for your buck.
- Mostly AI
This one is a little more complex and enterprise-oriented. On the contrary, if your team needs high-quality, scalable synthetic data, this is a solution that can be easily integrated, allowing you to preserve granular details while fully protecting privacy.
- Gretel
Gretel is a privacy-first, customisable tool for tabular and text data, making it a great option for developers looking for API-driven generation. If you’re a small business with development resources but not a huge data team, it also lets you integrate synthetic data generation programmatically, meaning you can automate the process without any big upfront infrastructure.
- Hazy
Hazy is another option, particularly for creating high-quality data for customer engagement and fraud modelling. Why is that important? Because they both rely on realistic, representative datasets, which can only really be achieved by synthetic data that accurately reflects real-world patterns.
- Mockaroo
Mockaroo is a simple online tool for quickly generating sample or synthetic data. It’s more user-friendly and accessible, but you’d lose the advanced integration and enterprise-level governance.
- Syntho
For small businesses looking for a cost-effective, self-service engine to generate synthetic data, Syntho is another good option. With its data-centric and powerful AI engine, it’s great for creating privacy-compliant datasets at scale – but it should be noted, it does have a high learning curve, which might be an issue if you’re new to tools like this or lack technical resources.
- YData Fabric
Lastly, we have YData Fabric, a tool that unifies data profiling and synthetic generation to enhance AI model performance, based on tabular, relational, and time-series data..
Conclusion
Those are seven tools that have been trending in the industry right now, but the one you choose should be dictated by your business market, your specific needs, and your technical resources. In our opinion, K2view is the most comprehensive and versatile, but for something as important as this, it’s recommended you do your own research and due diligence.
