Neha Tharani

Data Analyst/Engineer

This is an ongoing project where the task is to perform ETL on data generated by ERPs of various dealers and customers around the globe. The cleansed data is then consumed by a team of data scientists to create dashboards and perform various machine learning operations to identify current sales and future opportunities.

Created a new workflow using DAGs in Airflow for extracting source data and landing the data in Snowflake after processing it.

This project involved setting up the data pipelines and deploying agents in Azure DevOps for tasks that were previously handled using Cron jobs. These agents deploy internal repositories and packages on clusters and perform migrations among several environments, viz., Dev, QA, and Prod.

This provided a better view to the Project Managers and Project Owners in understanding the data flow and source of discrepancies.

Thoroughly tested the data flow by unit testing every function and integration testing the entire pipelines.

Created a Flask App-builder website for clients to log their data and to provide a feedback on current data. Creating this feedback loop reduced re-work and made the next steps in the pipeline, such as data processing and logic building much faster and efficient.

Created a website for the data engineering team to host their documentation, visualizations, and naming standards. The website is currently hosted internally.

The website was created using HTML, bootstrap, and Javascript. It converts markdown file from several projects into static webpages using MkDocs.

Hosting documentation on a central website made it easier for the team to read and contribute to documentation. It also enabled searching and sharing of documentation across several team and functions.

Master Thesis Student

Created awareness about Retirement Preparedness among the millennials by developing a web-based Retirement Planner with Avatars, Chatbot, and several other interactive features.

Devised Analysis Methodology for understanding the state of Retirement Preparedness of the Swiss Population.

The website was created using HTML5, CSS3, and Javascript. The analysis was done using R programming language and SPSS.

Business Intelligence Intern

Accelerated the monitoring of business process flow of the company by creating a data warehouse and a novel dashboard.

Helped the invested managers take hedging decisions 2x faster by creating a dashboard that displays exposure, contribution, and performance index of both single and multi-currency portfolios.

Senior Business Intelligence Associate

Enabled the HR team to keep track of various KPIs like attrition rate, joining rate, gender ratio, number of employees both nationally and internationally by cleaning and analysing the HR Data, creating and monitoring the dashboard.

Enhanced project allocation satisfaction of employees by 94% (from previous 62%) that displayed skills of employees, basic demographics and number of experience they have in those skills.