Here are the modules that make up DataSynthesis.
| Type | Usage/Implementation |
|---|---|
| DataTier | all the supported Database DDLs and Load Database scripts |
| DataTier APIs | Quarkus and Node based APIs to access datatier. This includes building, generating and processing capabilities |
| DataTier Web UI | Eventual user interface for DataSynthesis. |
As we thought about how to help healthcare we believed a focus on data being the asset was the path forward we needed to take and follow. As part of everything we do we want to ensure we are bringing forward data enablement capabilities.Our logic was simple, for years companies have focused on most aspects of development, from the tooling to developing the next generation of solutions to support their business needs and provide value. However, building great software to help today's modern needs require data, in many cases, massive amounts of production like data. While there are numerous other open source offerings out there we wanted to build something that could not only be used for traditional application based data needs but be used within integration effots as well. Since data is the electricity that powers business and the cornerstone of companies’ success in the digital era, we wanted to take a more comperehensive focus on enabling organizations around synthetic data.
With data being so critical, what is your companies focus on the need for meaningful realistic world based testing data? We kept seeing the "Data Driven Organization" term pop up and really wanted to know what companies and people meant. Again, we thought about synthetic data and how do we help build towards this. In order tp have a starting point we wanted to have some form of a defintion. To be a data-driven organization requires an overarching testing data culture that couples a number of elements, including high-quality production like data, broad access and data literacy along with appropriate data-driven decision-making governance and guidance processes. Companies that are successful in this space are quick at using data for all aspects of their business needs successfully and are quick to spot opportunities, quick to assess ideas and adapt quickly to test, learn and drive future capabilities and needs from these experiences. A data-driven organization does not have to come at a high price. While it sounds complicated it is really about providing businesses a means for data collection, cleansing, hosting and maintenance data while mitigating the risk of a data breach thru comprehensive testing processes and practices. Data-driven organization can innovate continuously because they understand and can embrace new business models quickly. Why should orgainzations risk data breaches or the potential leakage of PHI (in healthcare) or PII (In any other industry)? In today's technology world we wanted to enable a new and different way to innovate within a data-driven organization, synthetic data.
Synthetic data is defined as: "any production data applicable to a given situation that are not obtained by direct measurement" according to the McGraw-Hill Dictionary of Scientific and Technical Terms; where Craig S. Mullins, an expert in data management, defines production data as"information that is persistently stored and used by professionals to conduct business processes." With these definitions it is easy to understand the creation of synthetic data is an involved process that can be achieved by numerous measures and ways. Our way was to create a platform to synthesize data (Data Synthesis) for multiple needs based on items like industry standards, vendor data models, custom defined models all in an on-demand manner. The DataSynthesis platform is designed to generate and/or build upon the extensible data attributes it has. As the platform contnues to matture there will be more data attributes added as well. The idea for DataSynthesis is in NO WAY new or unique, it comes from the struggle that every organization with every resource on every project members of the Project Herophilus team have ever worked on across multiple industries.
Data Synthesis has always intended to be operated under the open/community source model. This means we are providing the code for community enhancements and improvements to support the growth of underlying data access capabilities. We are currently working on standing up the necessary artifacts. The code assets include a Web UI (at some point), APIs and the core repository patterns used to access the data structures offered within the platform. DataSynthesis open source licensing model is Apache-2.0.
DataSynthesis consists of four key areas.
At the core of DataSynthesis is the data tier that is designed to be extensible and support all the needs for the platform.
All things around the data tier are specifically contained within the link provided below.
DataTier
To support the needs of user requests are the data tier APIs. This API set is about being able to both generate data and persist it to the data tier.
These are intended to be minimal viable usable products that can be used to look at the datatier of DataSynthesis you implement.
Enjoy and Happy Coding!!!