Building Domain Based Data Management System

From the Director

Merlin S, EinNel Technologies

“The hardest part of AI and analytics is not AI, it’s data management”

– Greg Hanson

Since 2012, our software team has been providing engineering solutions to automotive design centers, manufacturing industries and other process industries. We have developed data-driven & AI based application for various scientific products. With our experience in building AI models, we have realized that data engineering is the crucial step in development of data-driven platforms. Hence at EinNel, we have built a strong team in data engineering adopting the latest digital technologies.

Domain Expertise is incredibly important to develop an innovative product in a specific domain, therefore we have put enormous efforts in developing data platforms which are domain centric. Currently our team is working on EinNel MDOx which is a data-driven platform designed to accommodate all the data relevant to the development of new vehicle. We strive to build a robust big data management system for storing domain-based model data in different data types and structures by availing technologies such as cloud data warehouse, data lakes, Apache Spark, and Kafka. By storing data with these systems, we will be able to quickly traverse through millions of data and support multiple workloads. It has also been a great experience for our team to design the pipeline that ingest data from static systems, process and transfer data between heterogenous data systems.