『Data Analytics Chat』のカバーアート

Data Analytics Chat

Data Analytics Chat

著者: Ben Parker
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🎧 Welcome to Data Analytics Chat – the podcast where data meets real careers.

Data isn’t just numbers; it’s a journey. Each episode, we explore a key topic shaping the world of data analytics while also discussing the career paths of our guests.

This podcast brings together top experts to share:

- Insights on today’s biggest data trends
- The challenges they’ve faced (and how they overcame them)
- Their career journeys, lessons learned, and advice for the next generation of data professionals

This is for anyone passionate about data and the people behind it.

👉 Hit subscribe and join us on the learning journey.


Connect with host - https://www.linkedin.com/in/ben---parker/

© 2025 Data Analytics Chat
マネジメント マネジメント・リーダーシップ 出世 就職活動 経済学
エピソード
  • Why Hiring And Retaining Top AI Talent Has Become Harder Than Ever
    2025/12/12

    In this episode of Data Analytics Chat, we welcome Misha Trubskyy, head of Claims Data Science at Mercury Insurance. Misha shares his journey from academia to corporate life, highlighting his transition from econometrics to leading data science initiatives in insurance. He discusses the significance of continuous learning, the challenges of AI and data implementation, and the importance of hiring and retaining top talent. Misha also delves into his leadership principles, the value of technical proficiency, and the importance of empathy in managing teams. Key issues such as the evolving hiring landscape, market conditions, and strategies for organizational growth are explored in-depth.

    00:00 Introduction and Personal Philosophy
    00:14 The Importance of Continuous Learning
    00:44 Challenges in the AI and Data Science Field
    01:20 Guest Introduction: Misha Ky
    02:24 Misha's Career Journey
    03:43 Current Excitements in AI and Data Science
    06:09 Navigating Human Elements in Claims
    07:37 Leadership Challenges and Lessons
    11:28 The Value of Individuality in Leadership
    19:31 Advice for Aspiring Data Leaders
    29:52 Hiring Challenges in AI and Data Science
    37:02 Finding the Right People for the Job
    37:23 The Importance of Critical Thinking
    37:41 Authenticity in Interviews
    38:26 The Role of Technology in Interviews
    38:51 Evaluating Candidates Beyond Technical Skills
    41:36 The Misconception About Technical Skills
    42:25 Personality and Attitude in Hiring
    44:21 Challenges in the Job Market
    48:55 Investing in Junior Staff
    01:04:33 Retention Strategies for Top Performers
    01:10:03 Future of the Hiring Landscape
    01:13:42 Conclusion and Final Thoughts

    Thank you for listening!

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    1 時間 11 分
  • Why Data Governance & Data Quality Are Important
    2025/12/04

    In this episode of Data Analytics Chat, we welcome Carol Kim, Executive Director at IBM, who shares her intriguing journey from a finance background to leading technology, data, and AI at IBM's Global Real Estate Organization. Carol talks about her career transformation, the importance of curiosity, authentic leadership, and the role of storytelling in decision-making. The episode also delves into the significance of data governance and quality for data-driven decision-making and how to build effective data governance frameworks. Carol further discusses adapting to different cultures, continuous reinvention, and the hidden costs of poor data quality. Tune in to get insights into navigating a tech-driven career and the pivotal role of data in modern enterprises.

    00:00 Introduction: The Power of Willingness to Learn
    01:12 Welcome to Data Analytics Chat
    02:01 Carol Kim's Career Journey
    02:57 The Role of Data in Real Estate
    03:38 Adapting to Different Cultures
    07:54 The Importance of Storytelling in Data
    09:59 Challenges in Leadership and Career Transitions
    15:13 The Significance of Data Governance and Quality
    24:06 Conclusion and Final Thoughts

    Thank you for listening!

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    25 分
  • The Rise of AI Agents
    2025/12/03

    In this episode of Data Analytics Chat, host Ben welcomes Ilya Meizin, SVP Head of AI Solutions at Dun & Bradstreet. Ilya shares his career journey from management consulting to leading AI solutions, highlighting the importance of implementation, continuous learning, and cross-domain expertise. He discusses the evolution of AI agents, their capabilities, and the shift from linear models to stateful, autonomous agents. The conversation delves into complexities of scaling AI, embedding agents in enterprise architecture, and balancing technical innovation with business value. Ilya also emphasizes the necessity of high-quality data and the role of collaboration across departments for successful AI deployment.

    00:00 Introduction and Initial Insights
    01:14 Guest Introduction and Career Overview
    02:45 Transition from Strategy to Implementation
    04:15 Learning and Adapting in Consulting
    05:35 Defining Career Moments
    10:35 Handling Challenges and Stress
    13:03 Leadership and Team Dynamics
    14:45 Balancing Technical and Business Skills
    20:01 Focus and Credibility in Leadership
    23:18 Introduction to AI Agents
    23:39 Capabilities of AI Agents
    24:22 Technical Aspects of AI Agents
    25:39 Complex Problem Solving with AI Agents
    28:40 High-Value Use Cases for AI Agents
    32:14 Team Collaboration in AI Deployment
    33:19 Challenges in Scaling AI Agents
    37:21 Data Quality and AI Agents
    45:12 Future of AI Agents in Enterprises
    48:17 Conclusion and Final Thoughts

    Thank you for listening!

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    49 分
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