Today for business continuation, the business model needs to represent in many ways - a normalized form for transactional data, a time-series database for process mining, a knowledge graph for semantics search or link data, a data-vault or snowflake model for data warehouse, a streaming model for the real-time event and columnar storage for machine learning. Automation needs to be in place to reduce repetition costs where the user will be focused more on data contracts, data quality, data profiling, etc.
I was not happy with the different cloud tools in the market so I decide to one myself. As a result, I wrote a low-code compiler where RDF can transfer to the schema, SQL statements, model visualization, data linage etc. Then I build UI where users don't need to write any source code. You will find many automation demo examples that I have prepared for different target users like data warehouses, knowledge graph engineers, and business analysts, and many others.
Developers will spend 90% of their time on data contracts, and data profiling instead of technical tooling. It is just 10 min of work to build different end-to-end data pipelines.
Looking forward to your feedback, suggestion, and contribution. If you found any bugs create an issue in the GitHub project. I hope I will give a fix within 2 weeks.
