Designed data quality visualizations and dashboards for summary view, plant view,
defect code analysis, LDO analysis, DQI Details-Logistics, and weekly trend, Spotfire is
used as the software to design & deploy the dashboard.
Ingested data from various data source like Infinity, Regulatory Data, and Enterprise
Material into AWS Cloud (Enterprise Data Lake) using Python.
Utilized python for Dynamic data analysis, filtering, deep data analysis and dynamic
color coding for trend & outlier.
Using R Capabilities perform defect code and trend analysis.
Develop Custom DQIs (Data Quality Indicators) as per businesses need.
Data Quality Dashboard enables business users to continuously monitor data quality,
view its current state, track trends, and use insight to make informed business decision.
Eliminated need for extensive verification of planning output.
Implemented report automation to reduce the manual labor hours and eliminated
process waste which led to cost savings.
Write back capabilities were implemented in Spotfire.