Indium supported the client in automating test cases for repetitive business workflows, carrying out data assurance for the platform’s functionalities, and proposing QA plan after thorough understanding of the data types at different stages of data flow.

Client is an Energy Analytics services provider that leverages Data Science/Machine Learning to deliver digital intelligence for renewable energy industry (solar and wind power infrastructure). The platform monitors live data from energy turbines and suggests operating performance/efficiency for forecast and maintenance. The app is built on a data management layer (Big Data) that is fed to training models (AI/ML) and outputs analytics data / data visualization for decision making. The platform integrates with cloud data sources.

• Data Assurance for the full portfolio of features: forecasting, performance insights and visualization.
• Understand the data mechanics at different stages, data preparation for specific use cases, exploration and visualization workflows and propose QA plan.
• Data quality validations on a continuous and periodic basis.
• Automate scenarios for repetitive business logic and Regression (maximum coverage).