Akhila Katepalli - Bio

Introduction to Me!

Hello! I’m Akhila, a graduate student pursuing MS in Business Analytics from the Carl H. Lindner College of Business, University of Cincinnati. For the past four years, I worked as a Data Analyst at Ugam Solutions, where the last position I held was that of a Senior Analyst. As a data analyst, I worked with retail business stakeholders from various multi-dimensional geographies like Australia and America solving day-to-day business problems with impactful data-driven solutions.

Academic Background

• Bachelor of Technology in Computer Science & Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham (University), Coimbatore, India.

Professional Background

• My work experience mostly comprised using transactional data from a retail business to improve customer experience and thereby boost customer retention.

• Through means such as building machine learning models to create targeted marketing strategies, coupons, and offers, and assess business performance and ongoing marketing initiatives through descriptive analysis using KPI dashboards, comprehensive reporting, and exploratory data analysis.

• These data-driven insights helped the business stakeholders with key decision-making when it came to improving the customer experience.

• I had mostly worked on SQL, R, and Excel doing various things ranging from answering simple business questions on an ad-hoc basis to building dashboards, and machine learning models.

• I want to up skill myself using advanced analytics methods and strengthen my knowledge of statistical concepts, and that’s what I am very much looking forward to from the Business Analytics program that I am currently pursuing at the University of Cincinnati.

Experience with R

I have been working with R for three years now. It was one of the most common tools that I used during my work experience as a data analyst. The most common functions that I performed using R were,

• Importing and exporting data from and to Excel.

• Manipulating these data frames (imported from Excel) as required.

• Building classification models such as logistic regression, decision tree, and random forest.

• Generating and automating Excel based dashboards i.e pulling data using ODBC connections, analyzing and summarizing data for KPIs, and exporting output in the form of Excel workbooks.

Experience with other analytics software

The other analytics software that I’ve had experience working with are Tableau, Google Analytics, Hue, Apache Zeppelin, snowflake, Amperity, AWS, and Amazon Redshift.

A bit of jazz!

# The weight and height of a person are as follows,
wt <- 150
ht <- 68
# Let's calculate BMI using the formula from Lab 1,
bm <- (wt*703)/(ht^2)

The BMI calculated for the height and weight as mentioned above is 22.8049308.