Stardata Manifesto
Eliminate data quality issues before they appear in Production, ensure and democratize data quality.
Why Data Is Bad?
- Siloed Teams
- Lack of Data Testing
- Lack of Data Pipeline Testing
- Lack of Data Monitoring in Production
DataOps approach to Data Quality:
Adopts DataOps to integrate Automated Data Testing in lower environments and Data Quality Monitoring in operations, shift-left approach of the data development life cycle.
We believe Automated Data Quality Monitorig and Tesing not only reduces the development costs but also eliminates data defects in production, improves the health of the data and eliminates data downtime and we came up with Stardq, a fully integrated, cost effective & scalable Automated Data Quality Monitorig and Tesing tool for your data ecosystem having Traditional data and Big data.
Our Company
Headquartered in Hyderabad, India established in 2023 by a team of Data Professionals to solve various challenges faced by organizations related to data centric projects and systems.
We have a team of developers, architects, analyst and consultants in India.
We are deeply committed and invested in the success of our clients and partners. Stardata team has excellent experience and understanding on the workings data centric systems such as Data Warehouse, ETL/ELT, Data migrations, Datamarts, Datalake/Datalakehouse, Bigdata, Datamesh, Streaming data, MDM, RDM, CRM, CDP and cloud based data & analytics.
