KRISHNATEJA NALLURI

I am highly motivated and eager to take on new challenges. I have a strong work ethic, can easily adapt, and am excellent at connecting with others. I am skilled at working independently and quickly picking up new skills.

• Microsoft Azure Data Engineer Associate (I576-8737), 01/2023, Present
• Tableau Essential Training - LinkedIn Learning, 03/2022, Present
• SQL for Data Analysis - LinkedIn Learning, 02/2022, Present
• Core Java - MAASMIND, 11/2018, Present

• FedEx Business Retention Analysis, 08/2022, 10/2022, For this project, the major business problem is how to increase the retention rate of at-risk medium business customers of FedEx Latin America. We used structured, unstructured, and external Twitter data retrieved through Twitter developer API. Conducted classification analysis with decision tree using Rapid Miner and gave recommendations on improving services that customers value most and delight the existing customers. Covid Storytelling using Tableau, 02/2022, 04/2022, Collected data about bed availability in hospitals from different states. Performed data clean-up and pre-formatting to simplify analysis. Created visualizations by comparing bed availability during deaths occurred by covid-19. Created stories and dashboards with Tableau using line graphs, bar graphs, and heat maps. Climate Change, 08/2021, 12/2021, Imported Python libraries (Pandas, Matplotlib, NumPy) to analyze and visualize Earth's past and present climate to predict future climate and respond to changes in natural and human-induced factors. Deployed the ARIMA model to make the predictions on temperature for a city over a year.

• Collected data about bed availability in hospitals from different states. Performed data clean-up and pre-formatting to simplify analysis. Created visualizations by comparing bed availability during deaths occurred by covid-19. Created stories and dashboards with Tableau using line graphs, bar graphs, and heat maps.

• Imported Python libraries (Pandas, Matplotlib, NumPy) to analyze and visualize Earth’s past and present climate to predict future climate and respond to changes in natural and human-induced factors. Deployed the ARIMA model to make the predictions on temperature for a city over a year.