Data Bytes Women in Data

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(Intro 00:00:00) Companies leaping into AI without solid data foundations.

(00:01:12) Importance of conferences for connecting and learning.

(00:01:26) Christina emphasizes energy and storytelling at tech conferences.

(00:02:17) LinkedIn connections making conference experiences better.

(00:02:33) Christina’s background at Google and Waze.

(00:03:13) Analytics ascendancy model explained.

(00:04:10) Common issue of companies jumping into AI prematurely.

(00:05:38) Importance of sequential steps in the analytics journey.

(00:06:23) Christina’s ACE framework (Advise, Create, Educate).

(00:07:06) Roles of advising, creating content, and educating.

(00:08:22) Handling C-suite pressure regarding AI hype.

(00:09:07) Evaluating current capabilities and setting expectations.

(00:10:27) Common pitfalls in the analytics journey.

(00:12:20) Challenges and risks in advanced analytics.

(00:13:57) Regulation and risk in finance and healthcare.

(00:14:59) Responsibility for assessing risk and regulation.

(00:15:19) Cross-functional nature of risk assessment.

(00:16:12) Advice on continuing the analytics journey.

(00:16:44) Maintaining a positive mindset and continuous learning.

(00:18:27) Future role of AI in analytics.

(00:19:41) AI’s potential and limitations in turbocharging analytics.

(00:21:49) Christina’s personal analytics journey.

(00:22:27) From studying statistics to founding Dare to Data.

(00:25:33) Advice for aspiring data professionals.

(00:25:37) Importance of curiosity, learning, and communication skills.

(00:27:14) Being a translator between business and technology.

(00:27:49) Christina’s SQL courses on LinkedIn Learning.

(00:28:35) Future courses and learning opportunities.


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(00:00:00) - Introduction by Sol Rashidi on data management challenges.(00:00:36) - Sadie welcomes Sol and discusses her background and accolades.
(00:02:21) - Sol addresses the impact of AI hype on C-suite roles and data governance.
(00:03:17) - Sol explains her approach to overcoming data challenges.(00:04:16) - Discussion on the evolving roles within the C-suite and the challenges of unclear division of labor.
(00:05:59) - Sol on the responsibilities of a chief AI officer and the practical challenges in strategy and delivery.
(00:07:05) - Sadie and Sol discuss the added complexity of new C-suite roles.
(00:08:16) - Sol outlines an ideal CDO role and its necessary scope.(00:10:58) - Sol discusses professional relationships within the C-suite and strategies for negotiation.
(00:14:28) - Sol promotes a course on transitioning from a practitioner to the C-suite.
(00:15:12) - Discussion on the challenges and strategies for effective leadership in the C-suite.
(00:18:23) - Sol on learning from failures and the importance of asking for what you want.
(00:21:17) - Discussion on why few women hold leadership positions and how to negotiate effectively.
(00:26:08) - Sadie discusses the role of tools like ChatGPT in professional communication.
(00:30:06) - Sol shares her plans post-retirement and her new book release.


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[00:00:00] Intro and discussion on information retrieval
[00:00:36] Sadie welcomes Harpreet, discussing his achievements and connections
[00:01:46] Early interactions and courses between Harpreet and Sadie
[00:02:27] Updates on Sadie's SQL course and new roles
[00:03:42] Harpreet discusses following curiosity in his career and AI's growth
[00:06:55] Future of data science roles and specialization within the field
[00:09:40] Unique skills of data scientists and transition to deep learning
[00:15:23] Discussion on benchmarks, datasets, and introduction to retrieval augmented generation (RAG)
[00:20:16] Explanation and potential applications of RAG models
[00:24:09] AI applications in various industries and predictions for future AI integration
[00:29:02] Harpreet's personal productivity gains from AI and new tools enhancing workflows
[00:34:58] Harpreet's podcast impact on his career and future plans
[00:40:44] Recommendations for staying updated in deep learning
[00:45:36] Harpreet invites listeners to join his new research initiative


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Intro [00:00:00]

Priscila discusses the importance of an accessible data infrastructure and data literacy.

[00:00:41] Sadie:

Introduction of Priscila Papazisis, her achievements and roles.

[00:01:06] Sadie:

Discussion on AI and data literacy strategies for organizations.

[00:01:27] Priscila:

Priscila responds about strategies for fostering data literacy in organizations.

[00:02:03] Priscila:

Importance of executive support in building a data-driven culture.

[00:02:36] Priscila:

Training programs for data literacy across various companies.

[00:03:05] Priscila:

Reiteration of the need for accessible data infrastructure.

[00:03:42] Priscila:

Emphasizes employee engagement with data for decision-making.

[00:04:12] Priscila:

Continuous improvement and promoting an environment for feedback.

[00:04:36] Sadie:

Challenges in providing and encouraging training in organizations.

[00:05:07] Priscila:

Finding time and interest for employee training in a busy schedule.

[00:06:25] Priscila:

Importance of understanding statistical concepts, data visualization, and AI in business.

[00:07:39] Priscila:

Critical thinking and application of AI and machine learning in business.

[00:08:20] Priscila:

Understanding industry trends and market dynamics.

[00:08:50] Sadie:

Priscila shares examples of business value from data literacy programs.

[00:09:10] Priscila:

Story about enhancing logistics in a health insurance company.

[00:10:23] Priscila:

The impact of data literacy programs she initiated.

[00:11:16] Priscila:

Operational improvements from data-driven decisions.

[00:12:42] Priscila:

Importance of practical results from data products.

[00:13:19] Priscila:

Engaging in continuous learning and leveraging data literacy.

[00:14:10] Sadie:

Discussing common pitfalls in implementing data and AI programs.

[00:14:28] Priscila:

Key challenges and advice for data and AI program implementation.

[00:16:45] Sadie:

Advice for individuals improving their data and AI literacy.

[00:17:09] Priscila:

Recommended resources and personal approaches to data literacy.

[00:18:37] Priscila:

Emphasis on data storytelling and problem-solving with data.

[00:20:42] Sadie:

The role of storytelling in data and AI.

[00:21:11] Sadie:

Priscila's journey into the data field.

[00:22:10] Priscila:

Career path and evolution in data roles.

[00:23:16] Priscila:

Contributions to the data community and networking.

[00:25:36] Sadie:

The value of community in data and AI.

[00:26:27] Sadie:

Final advice for women in data and AI careers.


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[00:00:00] - Ania discusses her approach to energy use and following curiosity without questioning its practicality.

[00:00:34] - Introduction of Ania Cwojdzinska as a vibrant member of the Women in Data community, mentioning her background and achievements.

[00:01:24] - Sadie asks Ania about the intersection of data science and psychology and how Ania incorporates both in her work.

[00:03:02] - Ania shares her journey into data science during her PhD, highlighting the benefits of interdisciplinary approaches.

[00:04:52] - Discussion on the rigors of academic research and its relevance to data careers.

[00:05:47] - Ania talks about her surprise at the continued use of Excel in industry and the transition from academia to industry.

[00:08:05] - Sadie inquires if Ania has started using Excel in her industry work.

[00:08:27] - Exploring Ania's growth mindset and whether it was innate or developed over time.

[00:10:46] - Ania discusses leading the growth group for Women in Data and the various activities and workshops they conduct.

[00:13:35] - The unique aspects of the Women in Data growth group and its contribution to the community.

[00:14:42] - The inclusivity and openness of the Women in Data community.

[00:15:33] - Ania reflects on her advice for women in data careers, emphasizing self-awareness and the blend of personal interests with professional skills.

[00:20:16] - Sadie thanks Ania for her mentorship and contributions to the community.

[00:20:45] - Ania shares her most proud accomplishments: fostering lifelong friendships and achieving self-contentment.

[00:24:31] - Sadie and Ania discuss redefining success and the importance of being comfortable and happy with oneself.


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Discussion on AI in Business


[00:01:00] Sadie introduces the main conversation topics.
[00:01:20] Cal shares his anticipation for future meetups.
[00:01:26] Discussion on the rapid developments in AI.
[00:02:03] Key indicators companies overlook when identifying AI opportunities.


[00:02:28] Cal elaborates on challenges and solutions in AI opportunity realization and measurement.
[00:03:41] Approaches to mapping out the value of AI projects.


[00:04:53] Sadie questions the average time to see benefits from AI implementation.
[00:05:52] Cal discusses AI implementation timelines and the importance of build vs. buy decisions.


[00:08:20] Discussion on successful integration of AI into workflows and overcoming adoption barriers.
[00:09:23] The role of AI literacy in preventing unintended consequences.


[00:13:08] Conversation shifts to responsible AI and baseline principles for ethical considerations.
[00:14:16] Cal emphasizes the comprehensive nature of responsible AI beyond ethics.


[00:20:33] Cal shares his journey to founding Panda Data and its acquisition.
[00:24:52] Discussion on navigating the challenges in highly regulated industries.
[00:27:41] Cal's personal motivations and overcoming obstacles.
[00:32:09] What's next for Cal at Further and the vision for AI auditing practice.


[00:36:14] Cal shares his personal goal of visiting 100 countries and its relevance to understanding AI and data science.




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