Ep 209: How Successful Transformation Is Driven By Data Engineering Excellence with Aginic



Published
This week on the Data Futurology podcast, we talk transformation and the importance of having data engineers to guide the strategy and agenda. To provide expert insights into this topic, we have the pleasure of hosting Richard Glew, Chief Technology Officer, and Natalia Dronova, Senior Data Analyst from Aginic.

Aginic is a consultancy that assists organisations with their transformation goals, providing expertise in analytics, agile, and the digital experience. Transformation remains a challenging goal, with research showing that most projects fail. Glew and Dronova discuss some of the reasons for this, which are many and varied, but according to Dronova, one of the big ones is that organisations make mistakes in their haste to transform quickly. “One of the challenges with transformation are the people that want everything done within six or eight months,” she said. “They want it now, and they’re finding shortcuts to try and make it happen that are hurting them in the long run. Then, a few years later, when you look at their stack, it’s all over the place.”

Dronova and Glew then go in-depth in discussing the structural problems that can affect transformation efforts, as well as the cultural problems across organisations – the impact that a focus on data governance can have on projects, for example, and why organisations need to move to a position of data enablement.

Finally, the two also discuss the role of the data engineer. As Glew said, traditionally the role has lagged behind that of the software engineer, but with more focus being placed on their role in transformation, the rapidity with which the role is evolving, and the relative scarcity of engineers resulting in higher salaries, now is a great time to consider a career in data engineering. “With the state of data engineering today, it’s the best time to get into it, because it’s still evolving and innovating really quickly.” Glew said.

Tune in to this deep and insightful discussion to learn more about the dynamics behind transformation and the role of the data engineer.

Enjoy the show!

Thank you to our sponsor, Talent Insights Group!

Connect with Richard https://www.linkedin.com/in/rlglew/
Connect with Natalia https://www.linkedin.com/in/nataliadronova/
Learn more about Aginic https://aginic.com/

Join us in Melbourne for Scaling AI with MLOPS: https://www.datafuturology.com/mlops

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

What we discussed:
00:00 Introduction
06:39 Do you recommend people to move throughout the stack in their careers? And if so, do you have an order of preference?
08:06 If you can give us a bit of an overview of that engineering, where do you see it and where's it at the moment?
11:48 Tell me a bit more about the distinction between, a check-in business or delivery and the stakeholders?
13:43 Are there any key differences that you see between the organizations that have the distinction of the business and the delivery teams? And the ones that don't? Are there for example, structural differences?
15:08 How have you seen the role change evolve? And where do you see it going?
16:53 As the role evolves, and I guess the discipline matures, do you think that there'll be parts of their engineering that will become a solved problem? Or will we get to a point where we have enough or too many data engineers where they're a hot commodity?
27:12 How do you see the business transformation or digital transformation as a broader umbrella? What are some of the issues that you see companies having in either embarking on that journey or successfully completing that journey?
38:48 We spoke before about data management is one of those areas. Could you tell us a little bit more about how those two intersect, and what that world looks like at the moment?

Listen to the Data Futurology Podcast on bit.ly/listen2DF
Category
Management
Be the first to comment