In many organisations, data scientists and data engineers exist as support staff. Data engineers are there to make data accessible to data scientists and data analysts, and data scientists are there to make use of that data to support the rest of the business.

But in helping everyone else in the business, data professionals can often forget to help themselves.

However, just as AI and machine learning can be used to help others in the organisation perform their jobs more effectively, there’s no reason why they can’t also be used to help data professionals excel in their own jobs. And as experts in applying these techniques, data scientists are perfectly placed to leverage them.

In this episode, Prof Barzan Mozafari joins Dr Genevieve Hayes to discuss how AI and machine learning are helping data professionals do their jobs more effectively.

Guest Bio

Prof. Barzan Mozafari is the co-founder and CEO of Keebo, a turn-key data learning platform for automating and accelerating enterprise analytics. He is also an Associate Professor of Computer Science at the University of Michigan and Prof. Barzan Mozafari is the co-founder and CEO of Keebo, a turn-key data learning platform for automating and accelerating enterprise analytics. He is also an Associate Professor of Computer Science at the University of Michigan and has won several awards for his research at the intersection of machine learning and database systems.

Highlights

(00:05) Meet Barzan Mozafari
(00:50) The role of AI in data engineering
(01:36) The birth of Keebo
(02:34) Challenges in modern data pipelines
(05:41) How Keebo optimizes data warehousing
(07:35) AI and ML techniques behind Keebo
(08:47) Reinforcement learning in practice
(16:23) Guardrails and safeguards in AI systems
(26:29) The build vs. buy dilemma
(36:03) Future trends in data science and AI
(39:36) Final advice for data scientists
(40:50) Closing remarks and contact information

Links

Keebo website
Connect with Barzan on LinkedIn
Connect with Genevieve on LinkedIn
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