Mounika Kandala

• Performed ad-hoc analysis and data manipulation on large and complex datasets using SQL.

• Reduced query retrieval time by automating tasks with PL/SQL scripts, stored procedures, and functions.

• Utilized regression analysis and inferential statistics to forecast sales using R, Tableau - R Integration, and Excel.

• Developed standards for performance metrics, data collection, data integrity, query design, and reporting format.

• Ensured high-quality and meaningful analytical output.

• Worked on performance improvement of reports and SQL tuning to minimize resource utilization in a production environment.

• Added alerts in splunk and performed actions in splunk for checking logs when there are production issues.

• Experience collaborating with cross-functional teams within and outside organizations.

• Gathered requirements from the stakeholders, administrative staff, and clinicians from Eskenazi Health IU.

• Extracted, integrated, and provisioned data from multiple sources like text files, comma separated files, and excel spreadsheets and large Data sets in the format of ipynb, CSV and JSON containing patient information, claims data and billing data with appropriate PI.

• Continuous monitoring of data for accuracy, integrity, and quality and retrieved the data from enterprise warehouse using SQL queries, reporting in SQL and Tableau and suggested solutions accordingly.

· Develop solutions to leverage ETL tools and identify opportunities for process improvements using Informatica and Python.

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· Conduct root cause analysis and resolve production problems and data issues.

• Worked on identifying the feasibility of different physical activities performed by Healthy and Parkinson’s group by using biosensors.

• Collected the data, retrieved, and performed extraction, data cleaning and manipulation with Python (NumPy, Pandas) programming and worked on pre-processing tasks like Normalization, treating the missing values.

• In addition, performed Data Accuracy, Data Analysis, Data Quality checks before and after loading the data.

• Analyzed the participants data using different Machine Learning Algorithms such as K-Nearest Neighbors, Support Vector Machine and Random Forest Models to evaluate the sensor usage and applied Tableau to visualize and interpret the patterns using time-series charts in python.

• Retrieved and worked on data obtained from multiple sources on how technology is helping Dementia & physicians in providing care.

• Conducted in-depth analysis and manipulation of large and complex datasets using SQL.

• Improved query performance by automating tasks through the use of PL/SQL scripts, stored procedures, and functions.

• Utilized regression analysis, inferential statistics, and tools like R, Tableau-R Integration, and Excel to predict sales.

• Established standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high-quality and meaningful analytical output.

• Enhanced report performance and optimized SQL queries to minimize resource usage in a production environment.

• Collaborated with cross-functional teams both internally and externally.

• Built multiple KPI dashboards for stakeholders to monitor demand forecast, capacity, and changes leveraging BI tools.