About Us

Bringing sanity back to data since 2019.

Is data really an asset?

Enterprise data is difficult. It’s hard to get under control. It’s costly to govern. It demands significant and risky investment to get it right. It introduces a whole suite of technologies to build and maintain. And in our era of Agile, data topic is still inherently waterfall. Yet, no automation and no digital transformation is possible without good data.

DataSingularity is born of over 20 years of observing the companies struggle and fail on their core data. We are committed to turning the challenge into success, replacing years of enterprise data programs with two-sprints-to-production, and expensive technology suites with one business-friendly, easy-to-maintain solution that caters to all of your data needs, from Master and Reference Data to knowledge discovery and metadata management.

We are a team of Enterprise Data Governance, Information Management, Data Integration, and User Experience professionals. We believe in data that is a real asset bringing real tangible revenue while keeping the total cost of ownership low. We believe in opensource, therefore the core of our solution will always be free and available for anyone to use and develop. And we believe that a delivery is worth a thousand sales presentations, therefore we are happy to demonstrate our solution on your own data, no strings attached.

Our data philosophy prescribes three principles:

Right Data In The Right Context For Each User
Turning Knowledge Into Data
Breaking out of data silos

Right Data in the Right Context for Each User

UX is important. DUX ( Data User Experience) is even more so. Just like UX, it drives user adoption and decreases to cost of change management. Each user should feel comfortable with the terms and values they see on the screen. The data needs to be exposed in context, while making sure there is no disconnect between contexts.

Turning knowledge into data

Turning data into knowledge is useful. But machines can only process data. To achieve full automation, the knowledge of human experts that helps them take decisions should be available to machines as data.

Data silos are not evil

Data silos are an inherent part of every complex organization. Breaking them is not only expensive, but also disruptive to the business and systems alike. Instead of breaking the data silos, we should break OUT of data silos - leaving each of them intact and introducing an “interpreter” that can arbitrate information exchange without disrupting business processes or systems.