Synthetic data use case: data sharing

Share data in synthetic form to eliminate data sharing challenges that you will face when sharing original (sensitive) data.

The old situation

Share original (sensitive) data

Many organization aim to realize data-driven innovation. Here, data is essential and typically needs to be shared internally or even externally to 3th parties as starting point. It is relatively simple: without data, no data-driven innovation and no collaboration opportunities. Here, specifically for the realization of data-driven innovation, having a strong foundation to access and share that relevant data is essential.

However, where many organizations have strong ERP and data management solutions in place, accessing that data (either by your own colleagues or by 3the party solution providers) results in challenges and insights and knowledge about potential available data-sharing solutions is limited.

Consequently, when working with sensitive data, organizations will face one or more data sharing challenges. One typical data-sharing challenge will be time consuming trajectories and overhead (costs), resulting from legal contracts & risk assessments. Another one that organization could experience is untouched valuable data that cannot be transformed into valuable insights. Furthermore, having no strong foundation to share data could result in project-stops or questionable data-access situations. Finally, it could result in a situation where all involved parties experience a loss of energy and motivation.

Time consuming trajectories and overhead (costs) from legal contracts & risk assessments
Untouched valuable datasets that cannot be transformed into valuable insight
No solution resulting in choosing between a project-stop or questionable data-access
Loss of energy from involved parties

OUR SOLUTION

Share data in synthetic form

Our solution: share synthetic data as alternative for sharing original data. This allows our customers to eliminate those aforementioned data-sharing challenges. Ultimately, this creates a strong foundation to realize data-driven innovation, but then, in an agile way. where data can be accessed and shared freely.

We see 2 formats for data-sharing solutions in practice:

Ad hoc synthetic data

We see ad-hoc data synthetisation when agility in data sharing is desirable. As alternatively to realizing data-driven innovation with original (sensitive) data, here one can realize data-driven innovation on synthetic data. This situation will boost agility by avoiding the data sharing hurdles one would normally face.

Setup a synthetic data warehouse

Many organizations have a data warehouse containing original (sensitive) data. Our suggestion would be to introduce a data warehouse with synthetic data next to the data warehouse with original data. Now, your employees (or even 3th parties) can easily access and share synthetic data from the synthetic data warehouse to realize data-driven innovation upon and will not face those data access hurdles.