In this episode of the Data Futurology podcast, where we delve into the world of Generative AI in recruitment. Our guests today are industry experts: Grant Wright, the General Manager of Marketplace and AI Products at Seek, and James Eichhorn, Principal Consultant for Data Engineering, Machine Learning, and Data Science at Talent Insights Group. Grant and James provide a wealth of insights into how Generative AI is transforming the recruitment landscape, both from a technology perspective and the human element.

In this episode of Data Futurology, Felipe Flores and Grant Case, Regional Vice President, Head of Sales Engineering - APJ at Dataiku delve into the realm of Generative AI and its applications in the business world. They kick off by underlining the vital role Generative AI plays in organisations, and then they explore the challenges that come along with adopting this technology.

In this informative podcast episode, Felipe Flores speaks with Jade Haar, the Head of Privacy and Data Ethics at National Australia Bank (NAB). Jade shares her inspiring journey into the field of data ethics, driven by her passion for doing right by people and contributing to the public good.

In this episode, Kendra Vant and Tracy Moore delve into the world of generative AI and its potential for unlocking commercial value. They kick off by addressing the excitement and hype surrounding generative AI technologies and emphasise the importance of grasping the fundamentals to extract real value from these advancements. 

In this episode, host Felipe Flores interviews Alan Lowthorpe, co-founder of Adaptive Data (who advise organisations on how to accelerate the value delivered from data and AI) and James Lecoutre, Director at Talent Insights Group as they delve into the world of data analytics and AI leadership, sharing insights on building successful teams, embracing diversity, fostering a growth mindset and navigating challenges in data analytics and AI.

This week on the Data Futurology podcast, we host Chad Sanderson, the Chief Operator of Data Quality Camp.

Over the ten years Sanderson has been involved in data, he has held key roles in companies including Convoy, a late-stage freight technology company, and Microsoft, where he worked on the AI platform team.

Sanderson’s experience with these companies made him realise that there was a need for a platform where data specialists could come together and discuss strategies for maintaining high-quality data in their organisations.

His group, Data Quality Camp, has since attracted nearly 8,000 members, and has become a real meeting place to discuss everything from the technical implementation of a data strategy, through to helping members find work in an increasingly dynamic and disrupted workplace environment.

On the podcast, Sanderson highlights the strategies he has seen to deliver high-quality data environments, some of the traps and pitfalls to avoid, and how data specialists can better engage with and gain buy-in from the other lines of business within the organisation.

For insights direct from someone at the heart of the data quality conversation, don’t miss this in-depth conversation with Chad Sanderson.

Join the Data Quality Camp on Slack (https://dataquality.camp/slack)

Connect with Chad: https://www.linkedin.com/in/chad-sanderson/

Thank you to our sponsor, Talent Insights Group!

Join us for our next events: Advancing AI and Data Engineering Sydney (5-7 September) and OpsWorld: Deploying Data & ML Products (Melbourne, 24-25 October): https://www.datafuturology.com/events 

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

At Data Futurology’s OpsWorld conference in March, a panel of experts came together to discuss the importance of getting measurements, processes and methodologies right to drive DataOps and MLOps across the organisation.

The panel consisted of Katherine Fowler, Head of Business Transformation at L’Occitane Australia, Amar Poddatooru, Head of Data and Technology at Australian Ethical, and Emyr James, Head of Data at Resolution Life and moderating the discussion was Andrew Aho, Regional Director, Data Platforms at InterSystems. It became a far-reaching discussion that started with methods to define and measure the ROI of data and analytics initiatives and how to get those projects off the ground. The discussion moved on to overhyped technologies in the data space, and then looked forward to what is on the horizon for the years ahead.

As the panel discussed, there is a lot of interest among consumers in some innovative technologies, including ChatGPT. This is in turn driving a lot of interest at the executive level at rolling out solutions that use these tools. However, without the right foundations in place, and without proper concern for the privacy and regulatory risks associated with these tools, they will cause the data team more headaches than they’re worth.

This panel discussion is essential for understanding how to structure a foundation for data success, be disciplined in deploying the available resources across the data team, gain executive buy-in, and then steadily build the practice up.

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) and OpsWorld: Deploying Data & ML Products (Melbourne, 24-25 October): https://www.datafuturology.com/events 

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

What we discussed

2:07: Felipe introduces the Measurements Thought Leaders panel and moderator, Andrew Aho.

3:48: How do you define and measure data and analytics ROI?

7:21: A discussion on metrics that help get data initiatives off the ground.

9:41: How a data leader needs to focus on the data platform, and articulate both the “big picture” view and the details.

12:35: As more organisations adopt ops, processes and methodologies, what challenges might people anticipate arising, and how can those be addressed?

17:24: What can data professionals do to help solve the change management challenge?

18:34: What are the challenges and impact of upcoming “silver bullet” technologies like ChatGPT?

20:16: What is currently overhyped in the data space (and why)?

24:03: What can we as data scientists do to ensure that we’re looking at the right risks and drawing accurate conclusions on what is right for the business?

26:13: If the goal is to focus on data science, how can we also keep experimentation and creativity going?

29:49: How do you estimate the value of change to get executive buy-in?

31:18: What upcoming developments and trends will emerge over the next five to ten years?

This week on the Data Futurology podcast, we welcome Orla Glynn, Executive – AI, Reporting, Insights and Automation Configuration at Telstra. Glynn leads one of the biggest groups of data specialists to drive innovative AI and analytics across the company.

At the recent Advancing AI event in Melbourne, we were privileged to have a presentation by Vinay Joseph, the Pre-Sales Lead for IDOL at OpenText in APAC.

Vinay gives an overview of the features of IDOL and how they can help data science teams bring automation and AI to the use of unstructured data. He presents a wide range of case studies and use cases. These include how law enforcement and the military, right through to news organisations and political campaigns might be able to use the data to draw real-time and in-depth insights that would otherwise be inaccessible.

This week on the Data Futurology podcast we host Paul Milinkovic, the APAC Regional Director for the leading data integration platform, StreamSets. Milinkovic joins us to share his insights into data engineers' challenges and the pipelines they manage and maintain.

One statistic really highlights just how challenging work environments have become for data engineers: 76 per cent of organisations have a pipeline break at least monthly and for 36 per cent, it's weekly. Rather than contributing strategically to their organisations, engineers split their time between diagnosis and repair, and building new pipelines. This costs the organisation, as half the time the engineer isn’t being used strategically. It also leads to cultures of over-working, burnout, and high levels of churn within the data engineering team.

Another challenge data teams struggle with is competing priorities. When multiple lines of business need pipelines developed, teams often need to triage to accommodate priority tasks, and this affects overall company outcomes. Being able to help organisations deliver a low or no-code environment that is highly visual and accessible to non-data specialists has been a critical benefit for organisations that have adopted StreamSets.

Milinkovic then shares two case studies where StreamSets has helped with overcoming these challenges. In one, a bank achieved a seemingly impossible task – becoming compliant with looming Consumer Data Act requirements within four months. Then, a second bank was able to leverage StreamSets to its data to detect and thwart $9 million in fraudulent activity in a single month.

For more deep insights into overcoming the challenges facing modern data engineering teams, tune into the podcast!

Links

Website: https://streamsets.com

Follow on LinkedIn: https://www.linkedin.com/company/streamsets/

Whitepapers: 

https://go.streamsets.com/Whitepaper-Dollars_and_Sense_UGLP.html?utm_medium=website&utm_source=DataFuturology&utm_campaign=eg_dollars_and_sense_of_dataops

https://go.streamsets.com/Whitepaper-Dollars_and_Sense_UGLP.html?utm_medium=website&utm_source=DataFuturology&utm_campaign=eg_dollars_and_sense_of_dataops

 lifting-the-lid-on-data-integration-UGLP.html?utm_medium=website&utm_source=DataFuturology&utm_campaign=eg_lifting_the_lid_on_data_integration">https://go.streamsets.com/230214-lifting-the-lid-on-data-integration-UGLP.html?utm_me[…]turology&utm_campaign=eg_lifting_the_lid_on_data_integration

What we discussed:

00:00 Introduction 

02:22: Felipe introduces Paul Milinkovic. 

03:38: Milinkovic shares his background and his history with data at various levels and applications. 

06:04: Milinkovic overviews StreamSets – when and why the company was founded, and what its core capabilities are. 

09:04: What are the main issues that StreamSets helps data engineering teams solve? 

12:57: How does StreamSets address traditional data pipeline design and build challenges? 

12:33: What are the benefits of having a solution that is visual and accessible to non-technical users? 

22:51: One of the common questions with the self-service approach to data is governance. How can that be handled while still allowing full flexibility? 

26:46: Data engineers care a great deal about the quality and accuracy of data and the platforms that it sits on. Milinkovic explains why it is so important that they have the tools to be able to deliver that to the organisation. 

31:24: What is the financial impact of data engineering teams spending as much time fixing pipelines as they are? 

33:49: Milinkovic shares some case studies and use cases to highlight the value of StreamSets’ approach to data engineering.