AIMultiple Tabular Synthetic Data Benchmark Methodology in '24
AIMultiple aims to help buyers identify the right synthetic data solution for their business.
AIMultiple’s first synthetic data benchmark will aim to help global Forbes 2000 businesses prepare tabular test data. The benchmark will assess these aspects for their businesses:
- Fidelity of the synthetic data
- Privacy; effectiveness in removing personal information from synthetic data
- Computational requirements
- Total cost of ownership
What will be the guiding principles?
What will be benchmarked?
Synthetic data generation technology. AIMultiple will upload its dataset and collect the synthetic data for the benchmark using the default parameters provided in the vendor’s API.
What is the benchmark dataset?
Our dataset needs to be representative of enterprise data. It will include tens of real-world datasets consisting of gigabytes of data.
What is required from the vendor solution?
Vendor solution is expected to replicate the provided datasets to prepare test data.
How will AIMultiple perform the benchmark?
AIMultiple’s synthetic data generation benchmark aims to closely match the preferences of buyers. AIMultiple will measure these metrics:
- Fidelity will be reduced to a single value by combining multiple metrics or by leveraging multiple metrics. Vendors will be consulted before finalizing the metric.
- Privacy will be treated in the same manner as fidelity.
- Computational requirements: Time to replicate the database will be tested with databases with gigabytes of records.
- Total cost of ownership: Vendors’ cost model or pricing will be shared to help buyers compare prices of different vendors. Vendors are not required to disclose their pricing to participate but disclosure can create more transparency for buyers.
- Customer service: Reviews on B2B review platforms will be analyzed to assess customer satisfaction.
How will the results be published?
They will be published on AIMultiple.com and will feature graphs that users can leverage to find the right vendor for their business. Different metrics will be separately presented to create transparency for buyers.
Each participant will receive their detailed database level results as well as the average results.
Please note that AIMultiple is in the design phase of the benchmark and changes will be made as AIMultiple gets end user feedback and finalizes the benchmark.
Reach out to AIMultiple team via firstname.lastname@example.org if you would like to participate in the AIMultiple synthetic data benchmark.
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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