Vidmantė Čižienė
I’m a data professional with over a decade of experience in data and information management, fueled by my "librarian gene" and a #lessmess mindset.
I kicked off my coding journey in my thirties, honing my skills as a data engineer in Python for data extraction and preprocessing in used car historical data reporting and ML solutions. My knack for structure, classification, and organizing data comes from my academic background, which includes a Master of Science in Communication from the University of Amsterdam and a Bachelor's in Information & Communication Science from Vilnius University.
Passionate about a #lessmess environment, I believe streamlined data is a win-win for businesses and data professionals. While I’m impressed by the latest tech for better data management, I know that sometimes all it takes is a few extra lines of code. At the end of the day, it’s really about the people and what we do to (and with) data on a daily basis.
Currently, I lead data and information management initiatives at Ignitis in the Wholesale Electricity department, leveraging my project management skills honed in public relations and communications. I have also participated in Women Go Tech and Empowering Girls to encourage youth and women to choose engineering and information technologies as a career path.
Session
Are you using Airflow or Pandas? Great! You've contributed to better data management at your organization.
The breakthrough of AI has reignited focus on high-quality data and effective data governance (not that scary as it sounds!) and management practices. AI needs fit-for-purpose data to reach its potential, and we already have powerful toolkit — like Airflow, Pandas, Matplotlib/Seaborn, or Great Expectations — to optimize workflows and ensure data quality.