BANA 7025-001: Spring 2026: Module 2 Lab

Synopsis

Hi! My name is Joanna Visoskis. I grew up in Pittsburgh, Pennsylvania but I currently live in Columbus, Ohio.

I’m currently pursuing my MBA online through the University of Cincinnati as part of a career transition into business. I am pursuing the Data Analytics Graduate Certificate alongside my MBA in hopes to transition into an analytics role. Throughout my coursework, I have developed a growing interest in data analytics and consumer/customer insights.

Academic Background

Professional Background

I have a professional background in education with a strong emphasis on data-driven decision-making. I worked in K-5 elementary education both as an Elementary Educator and Reading Specialist across multiple Central Ohio school sites and districts. I spent a majority of my time regularly administering and analyzing literacy assessments to gather student performance data in order to determine appropriate instructional interventions for students. This work required using data to make informed decisions about student placement, progress monitoring, and instructional adjustments, as well as presenting assessment results to key stakeholders such as teachers, administrators, and families.

During my graduate studies at The Ohio State University, I served as a Graduate Research Assistant on a literacy intervention research grant, where I was responsible for collecting and managing research data, adhering to experimental design protocols, and conducting statistical analysis using SPSS to evaluate intervention effectiveness. Together, these experiences strengthened my ability to analyze data in both applied and research settings and to communicate insights clearly to support evidence-based decisions.

Experience with R

I’m a beginner with R. This is my first course using R formally, and I’m excited to learn a workflow that helps me both analyze data and clearly communicate results.

Experience with other Analytic Software

  • SPSS (research analysis using experimental and A/B testing designs)
  • Excel (descriptive, predictive, and prescriptive analysis; Monte Carlo simulation; optimization modeling)
  • SQL (introductory exposure through coursework)