DataFramed

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Data is no longer just for coders. With the rise of low-code tools, more people across organizations can access data insights without needing programming skills. But how can companies leverage these tools effectively? And what steps should they take to integrate them into existing workflows while upskilling their teams? Michael Berthold is CEO and co-founder at KNIME, an open source data analytics company. He has more than 25 years of experience in data science, working in academia, most recently as a full professor at Konstanz University (Germany) and previously at University of California (Berkeley) and Carnegie Mellon, and in industry at Intel’s Neural Network Group, Utopy, and Tripos. Michael has published extensively on data analytics, machine learning, and artificial intelligence.In the episode, Adel and Michael explore low-code data science, the adoption of low-code data tools, the evolution of data science workflows, upskilling, low-code and code collaboration, data literacy, integration with AI and GenAI tools, the future of low-code data tools and much more. Links Mentioned in the Show:KNIMEConnect with MichaelCode Along: Low-Code Data Science and Analytics with KNIMECourse: Introduction to KNIMERelated Episode: No-Code LLMs In Practice with Birago Jones & Karthik Dinakar, CEO & CTO at PiensoNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Staying ahead means knowing what’s happening right now—not minutes or hours later. Real-time analytics promises to help teams react faster, make informed choices, and even predict issues before they arise. But implementing these systems is no small feat, and it requires careful alignment between technical capabilities and business needs. How do you ensure that real-time data actually drives impact? And what should organizations consider to make sure their real-time analytics investments lead to tangible benefits?Zuzanna Stamirowska is the CEO of Pathway.com - the fastest data processing engine on the market which makes real-time intelligence possible. Zuzanna is also the author of the state-of-the-art forecasting model for maritime trade published by the National Academy of Sciences of the USA. While working on this project she saw that the digitization of traditional industries was slowed down by the lack of a software infrastructure capable of doing automated reasoning on top of data streams, in real time. This was the spark to launch Pathway. She holds a Master’s degree in Economics and Public Policy from Sciences Po, Ecole Polytechnique, and ENSAE, as well as a PhD in Complexity Science..Hélène Stanway is Independent Advisor & Consultant at HMLS Consulting Ltd. Hélène is an award-winning and highly effective insurance leader with a proven track record in emerging technologies, innovation, operations, data, change, and digital transformation. Her passion for actively combining the human element, design, and innovation alongside technology has enabled companies in the global insurance market to embrace change by achieving their desired strategic goals, improving processes, increasing efficiency, and deploying relevant tools. With a special passion for IoT and Sensor Technology, Hélène is a perpetual learner, driven to help delegates succeed. In the episode, Richie, Zuzanna and Hélène explore real-time analytics, their operational impact, use-cases of real-time analytics across industries, the benefits of adopting real-time analytics, the key roles and stakeholders you need to make that happen, operational challenges, strategies for effective adoption, the real-time of the future, common pitfalls, and much more. Links Mentioned in the Show:PathwayConnect with Zuzanna and HélèneLiArticle: What are digital twins and why do we need them?Course: Time Series Analysis in Power BIRelated Episode: How Real Time Data Accelerates Business Outcomes with George TrujilloSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Understanding where the data you use comes from, how to use it responsibly, and how to maximize its value has become essential. But as data sources multiply, so do the complexities around data privacy, customization, and ownership. How can companies capture and leverage the right data to create meaningful customer experiences while respecting privacy? And as data drives more personalized interactions, what steps can businesses take to protect sensitive information and navigate the increasingly complex regulatory picture? Jonathan Bloch is CEO at Exchange Data International (EDI) and a seasoned businessman with 40 years experience in information provision. He started work in the newsletter industry and ran the US subsidiary of a UK public company before joining its main board as head of its publishing division. He has been a director and/or chair of several companies and is currently a non executive director of an FCA registered investment bank. In 1994 he founded Exchange Data International (EDI) a London based financial data provider. EDI now has over 450 clients across three continents and is based in the UK, USA, India and Morocco employing 500 people.Scott Voigt is CEO and co-founder at Fullstory. Scott has enjoyed helping early-stage software businesses grow since the mid 90s, when he helped launch and take public nFront—one of the world's first Internet banking service providers. Prior to co-founding Fullstory, Voigt led marketing at Silverpop before the company was acquired by IBM. Previously, he worked at Noro-Moseley Partners, the Southeast's largest Venture firm, and also served as COO at Innuvo, which was acquired by Google. Scott teamed up with two former Innuvo colleagues, and the group developed the earliest iterations of Fullstory to understand how an existing product was performing. It was quickly apparent that this new platform provided the greatest value—and the rest is history.In the episode, Richie, Jonathan and Scott explore first-party vs third-party data, protecting corporate data, behavioral data, personalization, data sourcing strategies, platforms for storage and sourcing, data privacy, synthetic data, regulations and compliance, the future of data collection and storage, and much more. Links Mentioned in the Show:FullstoryExchange Data InternationalConnect with Jonathan and ScottCourse: Understanding GDPRRelated Episode: How Data and AI are Changing Data Management with Jamie Lerner, CEO, President, and Chairman at QuantumSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile...

Machine learning and AI have become essential tools for delivering real-time solutions across industries. However, as these technologies scale, they bring their own set of challenges—complexity, data drift, latency, and the constant fight between innovation and reliability. How can we deploy models that not only enhance user experiences but also keep up with changing demands? And what does it take to ensure that these solutions are built to adapt, perform, and deliver value at scale?Rachita Naik is a Machine Learning (ML) Engineer at Lyft, Inc., and a recent graduate of Columbia University in New York. With two years of professional experience, Rachita is dedicated to creating impactful software solutions that leverage the power of Artificial Intelligence (AI) to solve real-world problems. At Lyft, Rachita focuses on developing and deploying robust ML models to enhance the ride-hailing industry’s pickup time reliability. She thrives on the challenge of addressing ML use cases at scale in dynamic environments, which has provided her with a deep understanding of practical challenges and the expertise to overcome them. Throughout her academic and professional journey, Rachita has honed a diverse skill set in AI and software engineering and remains eager to learn about new technologies and techniques to improve the quality and effectiveness of her work. In the episode, Adel and Rachita explore how machine learning is leveraged at Lyft, the primary use-cases of ML in ride-sharing, what goes into an ETA prediction pipeline, the challenges of building large scale ML systems, reinforcement learning for dynamic pricing, key skills for machine learning engineers, future trends across machine learning and generative AI and much more. Links Mentioned in the Show:Engineering at Lyft on MediumConnect with RachitaResearch Paper—A Better Match for Drivers and Riders: Reinforcement Learning at LyftCareer Track: Machine Learning EngineerRelated Episode: Why ML Projects Fail, and How to Ensure Success with Eric Siegel, Founder of Machine Learning Week, Former Columbia Professor, and Bestselling AuthorSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business