# #229: Modernising the ATO to drive cloud data capabilities, analytics, AI, and deliver innovation. With Ben Taylor, the Assistant Commissioner for Data Insights at the ATO

Page: https://stenobird.com/podcast/data-futurology-leadership-and-strategy/229-modernising-the-ato-to-drive-cloud-data-capabilities-analytics-ai-and-deliver-innovation-with-ben-taylor-the-assistant-commissioner-for-data-insights-at-the-ato
Text version: https://stenobird.com/podcast/data-futurology-leadership-and-strategy/229-modernising-the-ato-to-drive-cloud-data-capabilities-analytics-ai-and-deliver-innovation-with-ben-taylor-the-assistant-commissioner-for-data-insights-at-the-ato.md
Podcast: [Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science](https://stenobird.com/podcast/data-futurology-leadership-and-strategy)
Published: 2023-04-13T05:28:42+00:00
Episode link: https://podcasters.spotify.com/pod/show/datafuturology/episodes/229-Modernising-the-ATO-to-drive-cloud-data-capabilities--analytics--AI--and-deliver-innovation--With-Ben-Taylor--the-Assistant-Commissioner-for-Data-Insights-at-the-ATO-e229kiu
Audio file: https://anchor.fm/s/3fab060/podcast/play/68522014/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2023-3-13%2F60eaa54d-ce5d-6ef0-4be8-dc9ff0137ad9.mp3
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Duration seconds: 1832

## Resource

The ATO transitioned from a fragmented data landscape to a centralized, cloud-driven powerhouse by adopting an XOps approach. This session details how to integrate DevOps, DataOps, and ModelOps to move from being an 'order taker' to a strategic business partner.

## Highlights
- Main idea: Data, technology, and business must function as a unified triad to achieve successful digital transformation
- Practical takeaway: Implement XOps to bridge the gaps between isolated DevOps, DataOps, and ModelOps frameworks
- Failure mode: Centralizing functions without standardized testing and governance can lead to delivery delays and reduced product quality
- Main idea: Technical excellence is necessary but insufficient; operational efficiency and predictability are what build organizational trust
- Practical takeaway: Use automated monitoring and governance frameworks to ensure data accuracy and model efficacy in production

## Topics

ATO, XOps, Data Governance, Cloud Transformation, ModelOps, DataOps, DevOps, Artificial Intelligence, Data Strategy

## Chapters
- 12:40 — The ATO Data Triad: Taylor explains the shift from fragmented data ownership to a centralized model based on the intersection of business, technology, and data.
- 14:50 — Challenges of Centralization: An overview of the risks associated with a large-scale data branch, including single points of failure and the need to drive trust through quality.
- 17:00 — The Rise of XOps: How the ATO integrated DevOps, DataOps, and ModelOps to solve the problem of operating in isolated silos.
- 19:10 — Governance and Risk Management: Using automated pipelines and governance frameworks to manage high-stakes risks like GST fraud.
- 26:00 — Managing Data Chaos: Addressing the increasing complexity of metadata and the 'sense of chaos' caused by rising business demands.
- 28:10 — From Order Takers to Strategic Partners: The necessity of evolving operational frameworks to drive efficiency, predictability, and organizational credibility.

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## Transcript

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