In this episode, we deep dive to the challenges of scaling AI projects beyond the experimental phase and argue that adopting best practices is crucial to achieving sustainable AI/ML initiatives. This podcast highlights the benefits of using Kedro, an open-source Python framework developed by QuantumBlack Labs, which promotes best practices and fosters collaboration within teams, ultimately leading to faster development cycles, reduced technical debt, and increased productivity. We also mentioned other tools developed by QuantumBlack Labs, such as Brix, which further facilitate the use of Kedro by enabling teams to discover and reuse reusable pipeline assets.

In this episode, we deep dive to the challenges of scaling AI projects beyond the experimental phase and argue that adopting best practices is crucial to achieving sustainable AI/ML initiatives. This podcast highlights the benefits of using Kedro, an open-source Python framework developed by QuantumBlack Labs, which promotes best practices and fosters collaboration within teams, ultimately leading to faster development cycles, reduced technical debt, and increased productivity. We also mentioned other tools developed by QuantumBlack Labs, such as Brix, which further facilitate the use of Kedro by enabling teams to discover and reuse reusable pipeline assets.

The Mindful Analyst

Deep Dive 02 | Scalable AI Deployment Framework using Kedro

Imagine having the power to uncover the hidden factors behind sudden changes in your data. With Google Cloud’s BigQuery ML, that power is now in your hands. Introducing the Contribution Analysis model—an intelligent tool that reveals the key drivers of change, pinpointing the exact combinations of contributors that lead to unexpected results. Whether you’re monitoring telemetry in tech, optimizing sales in retail, or fine-tuning healthcare data, this tool can transform how you understand your data. Take clothing sales as an example—by comparing data from 2022 and 2023, you can uncover the reasons behind a sales spike. Was it the store location? The vendor? Maybe the product category or item description? With this feature, organizations across industries can dive deep into their data, unravel the mystery of fluctuations, and make smarter, data-driven decisions.

Imagine having the power to uncover the hidden factors behind sudden changes in your data. With Google Cloud’s BigQuery ML, that power is now in your hands. Introducing the Contribution Analysis model—an intelligent tool that reveals the key drivers of change, pinpointing the exact combinations of contributors that lead to unexpected results. Whether you’re monitoring telemetry in tech, optimizing sales in retail, or fine-tuning healthcare data, this tool can transform how you understand your data. Take clothing sales as an example—by comparing data from 2022 and 2023, you can uncover the reasons behind a sales spike. Was it the store location? The vendor? Maybe the product category or item description? With this feature, organizations across industries can dive deep into their data, unravel the mystery of fluctuations, and make smarter, data-driven decisions.

Deep Dive 01 | New Superpower for Analyst from Google Cloud BigQuery

This podcast contains the latest trend in data analytics and AI technology. Join the deep dive discussion without the headache to understand technical terms. Created using NotebookLM by Google.

This podcast contains the latest trend in data analytics and AI technology. Join the deep dive discussion without the headache to understand technical terms. Created using NotebookLM by Google.

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Deep Dive 02 | Scalable AI Deployment Framework using Kedro

Deep Dive 01 | New Superpower for Analyst from Google Cloud BigQuery