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Top Tamr Thought Leadership from Female CDOs and Data Leaders

Kathleen Maley and Barkha Saxena

1. Best Practices for the CDO and Data Leaders in Times of Change

Kathleen Maley, Former Head of Consumer & Digital Analytics @ KeyBank and Barkha Saxena, Chief Data Officer @ Poshmark

Kathleen Maley and Barkha Saxena share their perspectives about how to deal with uncertainty and change within a data organization and how they used data to lead change in their organizations. Watch now.

 

Salema Rice

2. Building Data Teams for Tomorrow’s Challenges

Salema Rice, CDO @ Geometric Results

Salema Rice dives into the people part of data, discussing the key elements for building effective data teams, how  agile methodology plays a role in modern data organizations, and how the combination of people, processes, and technology accelerates outcomes. Watch now. 

 

Kathleen Maley

3. It’s about solving a business problem, not the data

Kathleen Maley, Former Head of Consumer and Digital Analytics @ KeyBank

Kathleen Maley shares why she stopped using the term data driven, why aligning around a business problem is key for data and analytics teams, the role language plays in communicating with business colleagues, and what she’s learned as a female analytics leader. Take a listen. 

 

Stefanie Costa Leabo

4. Data and the City

Stefanie Costa Leabo, CDO @ City of Boston

Stefanie Costa Leabo, Chief Data Officer for the City of Boston, talks about her non-linear career path (she considered becoming a political science professor at one point), the tangible connection between her work and what happens outside of city hall, and how sharing data helps Boston’s residents better understand what’s going on in their city. Take a listen. 

 

 

Veda Bawo

5. Data as a Change Agent

Veda Bawo, Director of Data Governance @ Raymond James

Veda Bawo discusses some of the toughest challenges to deal with in handling data and digital transformation, such as convincing folks that it’s important to focus on data quality and to raise the bar with respect to data quality when they’re already time and resource constrained. Watch now.