#235: Maximising the productivity of the data-led enterprise with UNSW, EG Australia and Compare the Market

This week we bring you a special episode of the Data Futurology podcast, featuring the keynote panel from our OpsWorld conference earlier this year featuring guests at different levels of data maturity. They shared their stories of the journey to enabling and unlocking the true value of data self-service.. The panel featured Kate Carruthers, Chief Data & Insights Officer, UNSW Sydney. She shared the university's experience, which has had a mature data environment for several years. At the other end of the table was Conor O'Neill, Head of Data Science, Compare The Market. He represented an organisation that is rapidly addressing a lack of data maturity across the organisation. The third person on the panel was Arvee Manaog, Head of Enterprise Systems, Data & Information Management, and Integration, EG Australia. She shared insights on how to effectively get organisation-wide buy-in, and then effectively educate all stakeholders on how to effectively use self-service. The panel was wide-ranging, starting off with a discussion around best practices in data self-service, before moving on to an in-depth summary of how to effectively approach self-service from each level of data maturity. There was also a robust Q & A session at the end of the panel. Through the robust audience questions, the panellists discussed strategies for ensuring data trustworthiness in self-service. They also discussed how ROI is best measured with self-service data practices. Businesses of all sizes that want to maximise data value should look at effective self-service approaches. This panel provides invaluable insights into both getting started and continuing to innovate once the data environment has been fully modernised and transformed. Enjoy the show! Thank you to our sponsor, Talent Insights Group ! Join us for our next events Advancing AI and Data Engineering Sydney (5-7 September): Join our Slack Community: What we discussed: 2:07: Felipe introduces the three panelists. 3:19: Carruthers explains UNSW’s perspective around best practices in data self-service. 6:23: Manaog explains the challenges of secure self-service in EG Australia. 10:38: Manaog explains the initial steps EG Australia took to get started on the data self-service journey. 14:40: O’Neill describes some self-service approaches he's seen work well. 19:50: Carruthers describes how UNSW has kept engagement with DevOps-created dashboards and models high across the organisation. 22:50: The panel takes audience questions, with the first being “How do we influence and motivate data silo owners to share for indirect enterprise outcomes?” 27:07: How can a mature data organisation bring together data literacy and digital literacy across users? 28:11: For a less mature data organisation, how can data leads ensure data trustworthiness in self-service? 30:14: There are trade-offs involved in self-service models. How can those be managed in the pursuit of a self-service culture? 35:38: What are the most effective techniques for measuring ROI with self-service data practices? Key quotes: Manaog: “We’re using DataIQ. And it actually helps because it's easier for users. I got a good adoption rate for that because it’s possible to do drag and drop, there are recipes and users don't need to code. They can easily do their analysis, create their workflows and then come to the hub and say, can you productionise this?” O’Neill: “In one model, we're doing a hub and spoke approach, where we have champions placed within the business units. We are working with those champions to ensure that we understand how they're using the report. It’s not just what they want to see. But in practice, what are they doing with it?”

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#235: Maximising the productivity of the data-led enterprise with UNSW, EG Australia and Compare the Market is an episode from Data Futurology - Data Science, Machine Learning & Artificial Intelligence From Top Industry Leaders by Felipe Flores.

This episode is 00:39:52 long.

This episode was published on Jun 7, 2023.

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