Operationalizing Data Within Large Organizations


Large organizations are inherently different from young startups, or even medium-sized companies. They have usually been around longer, have stricter compliance requirements and company cultures that may go back generations.

What is the path to making large institutions data-driven and making it stick? What are the types of unique challenges that arise in these types of organizations, and how can data leaders and practitioners overcome them?

In this webinar, Maksim Pecherskiy, former CDO of the City of San Diego and lead data engineer for the Development Data Partnership at the World Bank will demystify the unique challenges to operationalizing data science within large organizations, how large organizations can get their data science practice off the ground as quickly as possible, and what are the best practices that facilitate a data-driven culture within large organizations.

Adel Nehme

Data Science Evangelist at DataCamp

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

Connect with Adel on LinkedIn and Twitter.

Maksim Pecherskiy

Data Engineer at World Bank

Maksim Pecherskiy works for the World Bank and is the lead data engineer for the Development Data Partnership. Previously, he served as the first Chief Data Officer for the City of San Diego and as a Code for America fellow working in Puerto Rico. Maksim bridges the gap between people contributing to the public good and the technology they need to succeed. He came to the US from Ukraine when he was 10 years old, lived in 5 countries, and speaks 3 languages.

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