Anand Kishore

Implemented Data Quality rules and Validation logic using SQL to detect and resolve duplicates, missing values, and inaccurate service information.
Developed interactive Power BI dashboards to visualize data quality KPIs, highlighting error trends and system inconsistencies.
Collaborated with cross-functional teams to create standardized data definitions, metadata documentation, and business glossaries, improving consistency in analytics across functions.
Performed root cause analysis on data quality issues, identified corrective actions and communicated results to stakeholders.
Defined rules and thresholds that need to be applied when evaluating the quality of incoming datasets from external sources.
Identified discrepancies between source systems and target systems by comparing datasets using various tools.
Identified gaps in current Data Quality policies and processes and proposed solutions for improvement.
Assisted in sharing insights and fostering understanding of metadata management, guiding teams on best practices to improve data governance and ensure effective data utilization.

• Analyzed large data sets to identify trends and patterns.
• Developed reports using data visualization tools for stakeholder presentations.
• Conducted data cleaning and validation to ensure accuracy.
• Provided insights through statistical analysis and forecasting models.

• Provided technical support for software and hardware issues to diverse customers.
• Documented customer interactions and solutions in support ticketing system diligently.
• Analyzed customer feedback to identify recurring issues and suggest improvements.