Yetunde Data and Ivan Danov both live in London, work at QuantumBlack, and develop Kedro which is an open-source MLOps project. Yetunde works as a Director of Product Management, while Ivan works as a Senior Principal Machine Learning Engineer and the Engineering Director of Kedro.

QuantumBlack, a McKinsey company is a data science and advanced analytics company that works with customers from various industries. QuantumBlack was founded in 2009 and has its headquarters in London, United Kingdom. The company became a part of McKinsey & Company, a global management consulting firm, in 2015, and now operates as part of McKinsey's global analytics practice.

Topics that we talk about:

• What Kedro is and what problems it solves
• Reasons why different groups of data practitioners use Kedro
• Differences between companies that use and don't use Kedro
• Companies that use Kedro in production e.g. Telksomsel (Indonesia's largest telecom) - blog post
• Data and statistics that describe the adoption of Kedro
• When to use Kedro vs. Jupyter Notebooks
• Running Kedro everywhere, on all clouds and on-premise using various Kedro plugins e.g. VertexAI, Azure ML, SageMaker - blog post
• Using data, analytics, and community-driven insights in the product development of Kedro e.g. Kedro-Telemetry, Github, online training
• Current challenges, milestones, and focus areas for Kedro e.g. simpler configuration
• Trends in the MLOps landscape e.g. so many MLOps tools, LLMOPs
• Integration between Iguazio & QuantumBlack, and its plans for Kedro

The podcast was recorded by Adam Kawa (GetInData).

Subscribe to Radio Data on Spotify, YouTube, and Google Podcasts to get notifications about future podcast episodes.

Find more about our data, analytics, cloud, and MLOps projects and services at getindata.com.

Hosted on Acast. See acast.com/privacy for more information.