DataTalks.Club

DataTalks.Club
  • 5.0(7개의 평가)
  • 과학 기술
  • 매주 업데이트

DataTalks.Club - the place to talk about data!

  1. 1일 전

    How to Rebuild Data Trust? Mindful Data Strategy and Maintenance vs Innovation - Lior Barak

    Struggling with data trust issues, dashboard drama, or constant pipeline firefighting? In this deep‑dive interview, Lior Barak shows you how to shift from a reactive “fix‑it” culture to a mindful, impact‑driven practice rooted in Zen/Wabi‑Sabi principles. You’ll learn: Why 97 % of CEOs say they use data, but only 24 % call themselves data‑driven The traffic‑light dashboard pattern (green / yellow / red) that instantly tells execs whether numbers are safe to use A practical rule for balancing maintenance, rollout, and innovation—and avoiding team burnout How to quantify ROI on data products, kill failing legacy systems, and handle ad‑hoc exec requests without derailing roadmaps Turning “imperfect” data into business value with mindful communication, root‑cause logs, and automated incident review loops 🕒 TIMECODES 00:00 Community and mindful data strategy 04:06 Career journey and product management insights 08:03 Wabi-sabi data and the trust crisis 11:47 AI, data imperfection, and trust challenges 20:05 Trust crisis examples and root cause analysis 25:06 Regaining trust through mindful data management 30:47 Traffic light system and effective communication 37:41 Communication gaps and team workload balance 39:58 Maintenance stress and embracing Zen mindset 49:29 Accepting imperfection and measuring impact 56:19 Legacy systems and managing executive requests 01:00:23 Role guidance and closing reflections 🔗 Connect with Lior LinkedIn - https://www.linkedin.com/in/liorbarak Website - https://cookingdata.substack.com/ Cooking Data newsletter: https://cookingdata.substack.com/ Product product lifecycle manager: https://app--data-product-lifecycle-manager-c81b10bb.base44.app/ 🔗 Connect with DataTalks.Club Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/u/0/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ Check other upcoming events - https://lu.ma/dtc-events GitHub: https://github.com/DataTalksClub LinkedIn - https://www.linkedin.com/company/datatalks-club/ Twitter - https://x.com/DataTalksClub Website - https://datatalks.club/ 🔗 Connect with Alexey Twitter - https://x.com/Al_Grigor Linkedin - https://www.linkedin.com/in/agrigorev/

    1시간 2분

  2. 8월 1일

    From Simulations to Freelance Data Engineering: Orell's Journey Out of Academia and Into Consulting - Orell Garten

    In this episode, we talk with Orell about his journey from electrical engineering to freelancing in data engineering. Exploring lessons from startup life, working with messy industrial data, the realities of freelancing, and how to stay up to date with new tools. Topics covered: Why Orel left a PhD and a simulation‑focused start‑up after Covid hitWhat he learned trying (and failing) to commercialise medical‑imaging simulationsThe first freelance project and the long, quiet months that followedHow he now finds clients, keeps projects small and delivers value quicklyTypical work he does for industrial companies: parsing messy machine logs, building simple pipelines, adding structure laterFavorite everyday tools (Python, DuckDB, a bit of C++) and the habit of blocking time for learningAdvice for anyone thinking about freelancing: cash runway, networking, and focusing on problems rather than “perfect” tech choices A practical conversation for listeners who are curious about moving from research or permanent roles into freelance data engineering. 🕒 TIMECODES 0:00 Orel’s career and move to freelancing 9:04 Startup experience and data engineering lessons 16:05 Academia vs. startups and starting freelancing 25:33 Early freelancing challenges and networking 34:22 Freelance data engineering and messy industrial data 43:27 Staying practical, learning tools, and growth 50:33 Freelancing challenges and client acquisition 58:37 Tools, problem-solving, and manual work 🔗 CONNECT WITH ORELL Twitter - https://bsky.app/profile/orgarten.bsk... LinkedIn - / ogarten Github - https://github.com/orgarten Website - https://orellgarten.com 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/... Check other upcoming events - https://lu.ma/dtc-events GitHub: https://github.com/DataTalksClub LinkedIn - / datatalks-club Twitter - / datatalksclub Website - https://datatalks.club/ 🔗 CONNECT WITH ALEXEY Connect with Alexey Twitter - / al_grigor Linkedin - / agrigorev

    58분

  3. 7월 25일

    Can You Quit Your Job and Still Succeed as a Data Freelancer?

    Thinking about swapping your 9‑to‑5 for client work, but worried that a long German–style notice period will kill your chances?  In this live interview, seven‑year data‑freelance veteran Dimitri walks through his experience of taking his freelance career to the next level. About the Speaker: Dimitri Visnadi is an independent data consultant with a focus on data strategy. He has been consulting companies leading the marketing data space such as Unilever, Ferrero, Heineken, and Red Bull. He has lived and worked in 6 countries across Europe in both corporate and startup organizations. He was part of data departments at Hewlett-Packard (HP) and a Google partnered consulting firm where he was working on data products and strategy. Having received a Masters in Business Analytics with Computer Science from University College London and a Bachelor in Business Administration from John Cabot University, Dimitri still has close ties to academia and holds a mentor position in entrepreneurship at both institutions. 🕒 TIMECODES00:00 Dimitri’s journey from corporate to freelance data specialist05:41 Job tenure trends, tech career shifts, and freelance types10:50 Freelancing challenges, success, and finding clients17:33 Freelance market trends and Dimitri’s job board23:51 Starting points, top freelance skills, and market insights32:48 Building a lifestyle business: scaling and work-life balance45:30 Data Freelancer course and marketing for freelancers48:33 Subscription services and managing client relationships56:47 Pricing models and transitioning advice1:01:02 Notice periods, networking, and risks in freelancing transition 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/... Check other upcoming events - https://lu.ma/dtc-events LinkedIn - / datatalks-club Twitter - / datatalksclub Website - https://datatalks.club/ 🔗 CONNECT WITH DIMITRI Linkedin - https://www.linkedin.com/in/visnadi/

    58분

  4. 5월 26일

    From Hackathons to Developer Advocacy - Will Russel

    In this podcast episode, we talked with Will Russell about From Hackathons to Developer Advocacy. About the Speaker: Will Russell is a Developer Advocate at Kestra, known for his videos on workflow orchestration. Previously, Will built open source education programs to help up and coming developers make their first contributions in open source. With a passion for developer education, Will creates technical video content and documentation that makes technologies more approachable for developers. In this episode, we sit down with Will—developer advocate, content creator, and passionate community builder. We’ll hear about his unique path through tech, the lessons he’s learned, and his approach to making complex topics accessible and engaging. Whether you’re curious about open source, hackathons, or what it’s like to bridge the gap between developers and the broader tech community, this conversation is full of insights and inspiration. 🕒 TIMECODES 0:00 Introduction, career journeys, and video setup and workflow 10:41 From hackathons to open source: Early experiences and learning 16:04 Becoming a hackathon organizer and the value of soft skills 23:18 How to organize a hackathon, memorable projects, and creativity 33:39 Major League Hacking: Building community and scaling student programs 41:16 Mentorship, development environments, and onboarding in open source 49:14 Developer advocacy, content strategy, and video tips 57:16 Will’s current projects and future plans for content creation 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ Check other upcoming events - https://lu.ma/dtc-events LinkedIn - https://www.linkedin.com/company/datatalks-club/ Twitter - https://twitter.com/DataTalksClub Website - https://datatalks.club/ 🔗 CONNECT WITH WILL LinkedIn - https://www.linkedin.com/in/wrussell1999/ Twitter - https://x.com/wrussell1999 GitHub - https://github.com/wrussell1999 Website - https://wrussell.co.uk/

    57분

  5. 5월 9일

    Build a Strong Career in Data - Lavanya Gupta

    In this podcast episode, we talked with Lavanya Gupta about Building a Strong Career in Data. About the Speaker: Lavanya is a Carnegie Mellon University (CMU) alumni of the Language Technologies Institute (LTI). She works as a Sr. AI/ML Applied Associate at JPMorgan Chase in their specialized Machine Learning Center of Excellence (MLCOE) vertical. Her latest research on long-context evaluation of LLMs was published in EMNLP 2024. In addition to having a strong industrial research background of 5+ years, she is also an enthusiastic technical speaker. She has delivered talks at events such as Women in Data Science (WiDS) 2021, PyData, Illuminate AI 2021, TensorFlow User Group (TFUG), and MindHack! Summit. She also serves as a reviewer at top-tier NLP conferences (NeurIPS 2024, ICLR 2025, NAACL 2025). Additionally, through her collaborations with various prestigious organizations, like Anita BOrg and Women in Coding and Data Science (WiCDS), she is committed to mentoring aspiring machine learning enthusiasts. In this episode, we talk about Lavanya Gupta’s journey from software engineer to AI researcher. She shares how hackathons sparked her passion for machine learning, her transition into NLP, and her current work benchmarking large language models in finance. Tune in for practical insights on building a strong data career and navigating the evolving AI landscape. 🕒 TIMECODES 00:00 Lavanya’s journey from software engineer to AI researcher 10:15 Benchmarking long context language models 12:36 Limitations of large context models in real domains 14:54 Handling large documents and publishing research in industry 19:45 Building a data science career: publications, motivation, and mentorship 25:01 Self-learning, hackathons, and networking 33:24 Community work and Kaggle projects 37:32 Mentorship and open-ended guidance 51:28 Building a strong data science portfolio 🔗 CONNECT WITH LAVANYALinkedIn -   / lgupta18  🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/... Check other upcoming events - https://lu.ma/dtc-events LinkedIn -   / datatalks-club   Twitter -   / datatalksclub   Website - https://datatalks.club/

    52분

  6. 4월 4일

    From Supply Chain Management to Digital Warehousing and FinOps - Eddy Zulkifly

    In this podcast episode, we talked with Eddy Zulkifly about From Supply Chain Management to Digital Warehousing and FinOps About the Speaker: Eddy Zulkifly is a Staff Data Engineer at Kinaxis, building robust data platforms across Google Cloud, Azure, and AWS. With a decade of experience in data, he actively shares his expertise as a Mentor on ADPList and Teaching Assistant at Uplimit. Previously, he was a Senior Data Engineer at Home Depot, specializing in e-commerce and supply chain analytics. Currently pursuing a Master’s in Analytics at the Georgia Institute of Technology, Eddy is also passionate about open-source data projects and enjoys watching/exploring the analytics behind the Fantasy Premier League. In this episode, we dive into the world of data engineering and FinOps with Eddy Zulkifly, Staff Data Engineer at Kinaxis. Eddy shares his unconventional career journey—from optimizing physical warehouses with Excel to building digital data platforms in the cloud. 🕒 TIMECODES 0:00 Eddy’s career journey: From supply chain to data engineering 8:18 Tools & learning: Excel, Docker, and transitioning to data engineering 21:57 Physical vs. digital warehousing: Analogies and key differences 31:40 Introduction to FinOps: Cloud cost optimization and vendor negotiations 40:18 Resources for FinOps: Certifications and the FinOps Foundation 45:12 Standardizing cloud cost reporting across AWS/GCP/Azure 50:04 Eddy’s master’s degree and closing thoughts 🔗 CONNECT WITH EDDY Twitter - https://x.com/eddarief Linkedin - https://www.linkedin.com/in/eddyzulkifly/ Github: https://github.com/eyzyly/eyzyly ADPList: https://adplist.org/mentors/eddy-zulkifly 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ Check other upcoming events - https://lu.ma/dtc-events LinkedIn - https://www.linkedin.com/company/datatalks-club/ Twitter - https://twitter.com/DataTalksClub Website - https://datatalks.club/

    52분

  7. 3월 21일

    Data Intensive AI - Bartosz Mikulski

    In this podcast episode, we talked with Bartosz Mikulski about Data Intensive AI. About the Speaker: Bartosz is an AI and data engineer. He specializes in moving AI projects from the good-enough-for-a-demo phase to production by building a testing infrastructure and fixing the issues detected by tests. On top of that, he teaches programmers and non-programmers how to use AI. He contributed one chapter to the book 97 Things Every Data Engineer Should Know, and he was a speaker at several conferences, including Data Natives, Berlin Buzzwords, and Global AI Developer Days.  In this episode, we discuss Bartosz’s career journey, the importance of testing in data pipelines, and how AI tools like ChatGPT and Cursor are transforming development workflows. From prompt engineering to building Chrome extensions with AI, we dive into practical use cases, tools, and insights for anyone working in data-intensive AI projects. Whether you’re a data engineer, AI enthusiast, or just curious about the future of AI in tech, this episode offers valuable takeaways and real-world experiences. 0:00 Introduction to Bartosz and his background 4:00 Bartosz’s career journey from Java development to AI engineering 9:05 The importance of testing in data engineering 11:19 How to create tests for data pipelines 13:14 Tools and approaches for testing data pipelines 17:10 Choosing Spark for data engineering projects 19:05 The connection between data engineering and AI tools 21:39 Use cases of AI in data engineering and MLOps 25:13 Prompt engineering techniques and best practices 31:45 Prompt compression and caching in AI models 33:35 Thoughts on DeepSeek and open-source AI models 35:54 Using AI for lead classification and LinkedIn automation 41:04 Building Chrome extensions with AI integration 43:51 Comparing Cursor and GitHub Copilot for coding 47:11 Using ChatGPT and Perplexity for AI-assisted tasks 52:09 Hosting static websites and using AI for development 54:27 How blogging helps attract clients and share knowledge 58:15 Using AI to assist with writing and content creation 🔗 CONNECT WITH Bartosz LinkedIn: https://www.linkedin.com/in/mikulskibartosz/ Github: https://github.com/mikulskibartosz Website: https://mikulskibartosz.name/blog/ 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ Check other upcoming events - https://lu.ma/dtc-events LinkedIn - https://www.linkedin.com/company/datatalks-club/ Twitter - https://twitter.com/DataTalksClub Website - https://datatalks.club/

    55분

  8. 3월 14일

    MLOps in Corporations and Startups - Nemanja Radojkovic

    In this podcast episode, we talked with Nemanja Radojkovic about MLOps in Corporations and Startups. About the Speaker: Nemanja Radojkovic is Senior Machine Learning Engineer at Euroclear. In this event,we’re diving into the world of MLOps, comparing life in startups versus big corporations. Joining us again is Nemanja, a seasoned machine learning engineer with experience spanning Fortune 500 companies and agile startups. We explore the challenges of scaling MLOps on a shoestring budget, the trade-offs between corporate stability and startup agility, and practical advice for engineers deciding between these two career paths. Whether you’re navigating legacy frameworks or experimenting with cutting-edge tools. 1:00 MLOps in corporations versus startups 6:03 The agility and pace of startups 7:54 MLOps on a shoestring budget 12:54 Cloud solutions for startups 15:06 Challenges of cloud complexity versus on-premise 19:19 Selecting tools and avoiding vendor lock-in 22:22 Choosing between a startup and a corporation 27:30 Flexibility and risks in startups 29:37 Bureaucracy and processes in corporations 33:17 The role of frameworks in corporations 34:32 Advantages of large teams in corporations 40:01 Challenges of technical debt in startups 43:12 Career advice for junior data scientists 44:10 Tools and frameworks for MLOps projects 49:00 Balancing new and old technologies in skill development 55:43 Data engineering challenges and reliability in LLMs 57:09 On-premise vs. cloud solutions in data-sensitive industries 59:29 Alternatives like Dask for distributed systems 🔗 CONNECT WITH NEMANJA LinkedIn -   / radojkovic   Github - https://github.com/baskervilski 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/... Check other upcoming events - https://lu.ma/dtc-events  LinkedIn -   / datatalks-club    Twitter -   / datatalksclub    Website - https://datatalks.club/

    58분
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DataTalks.Club - the place to talk about data!

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  • 제작진
    DataTalks.Club
  • 방송 연도
    2020년 - 2025년
  • 에피소드
    187
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    전체 연령 사용가
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