Managing Data for Effective GenAI Application // Anu Arora and Anass Bensrhir // #215

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Mar 5, 2024

Explore the impact of GenAI on industries and challenges in scaling, data quality hindrances, and non-value-added tasks. Delve into the evolving role of data engineers, LLM integration, and GenAI tools for automation and data handling. Discuss risks with LLM models in AI applications, emphasizing data privacy, compliance, and decision-making strategies.

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Introduction

00:00 • 6min

Exploring Data Careers and Gen. AI Impact on Data Engineering

05:39 • 4min

Harnessing the Power of Data for Competitive Advantage

09:31 • 13min

Exploring the Evolving Role of Data Engineers and the Integration of LLMs in Data Engineering

22:13 • 3min

Utilizing GenAI for Data Handling and Automation

24:56 • 4min

Navigating Risks with LLM Models in AI Applications

29:17 • 22min

Anass Bensrhir is the Associate Partner of McKinsey & Company Casablanca. Anu Arora is the Principal Data Engineering at McKinsey & Company.

Check out mckinsey.com/quantumblack MLOps podcast #214 with QuantumBlack AI by McKinsey's Principal Data Engineer, Anu Arora and Associate Partner, Anass Bensrhir, Managing Data for Effective GenAI Application brought to you by our Premium Brand Partner QuantumBlack AI by @McKinsey . // Abstract Generative AI is poised to bring impact across all industries and business functions across industries While many companies pilot GenAI, only a few have deployed GenAI use cases, e.g., retailers are producing videos to answer common customer questions using ChatGPT. A majority of organizations are facing challenges to industrialize and scale, with data being one of the biggest inhibitors. Organizations need to strengthen their data foundations given that among leading organizations, 72% noted managing data among the top challenges preventing them from scaling impact. Furthermore, leaders noticed that +31% of their staff's time is spent on non-value-added tasks due to poor data quality and availability issues. // Bio Anu Arora Data architect(~12 years) and have experience in Big data technologies, API development, building scalable data pipelines including DevOps and DataOps, and building GenAI solutions. Anass Bensrhir Anass Leads QuantumBlack in Africa, he specializes in the Financial sector and helps organizations deliver successful large Data transformation programs. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Website: https://www.mckinsey.com/capabilities/quantumblack/how-we-help-clients --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Anu on LinkedIn: https://uk.linkedin.com/in/anu-arora-072012 Connect with Anass on LinkedIn: https://www.linkedin.com/in/abensrhir/ Timestamps: [00:00] Anass and Anu's preferred coffee [00:35] Takeaways [04:02] Please like, share, leave a review, and subscribe to our MLOps channels! [04:09] Huge shout out to our sponsor QuantumBlack! [04:29] Anu's tech background [06:31] Anass tech background [07:28] The landscape of data [10:37] Dealing with unstructured data [15:51] Data lakes and ETL processes [22:19] Data Engineers' Heavy Workload [29:49] Data privacy and PII in the new LLMs paradigm [36:13] Balancing LLM Adoption Risk [44:06] Effective LMS Implementation Strategy [49:00] Decisions: Create or Wait [50:39] Wrap up