The question arose as to the correct way to model address data. Michael Olschimke explained his point of view and shared his idea on how to proceed in the latest session of Data Vault Friday. You can find the video either here in the classroom or below. How would you model address data? Would you do it differently to Michael?

Klarna is planning to halve its workforce, leveraging AI to boost productivity ahead of a potential IPO. They've already trimmed from 5,000 to 3,800 employees, with more cuts likely. **Question for you:** What do you think of this from an ethical perspective? Would you let AI run your team? 🤔

Hey everyone, I'm curious to know—what was your entry point into the world of data? For me, it all began with Fantasy Football. I wanted to create my own stat analytics, so I started querying player databases using an API. There’s so much to analyze in American Football, and with our fantasy draft kicking off this Sunday, I’m reminded of those early days. So, what was your first data project? How did you get started? Looking forward to hearing your stories!

Explore different options for building RAG with IBM watsonx and learn advanced techniques for achieving accurate and cost-effective solutions. Thursday, 29th August | 3pm-3:45pm AEST Register Link: https://info.techdatacloud.com.au/ibm-ai-webinar-series-lets-build-rag-in-watsonx-with-optimal-accuracy-and-cost-aug2024

Interest to hear what tools you use to Master Messy Data? This webinar on Snowflake Integration with Gigasheet might be of interest if you use Snowflake. Some of the points covered include: Gigasheet enables easy integration with Snowflake, allowing Data Engineers to work with large datasets without needing advanced coding skills like SQL or Python. The platform provides powerful, user-friendly tools for cleaning and transforming messy data, including features like cross-file lookups and data type corrections, making it easier to prepare data for analysis. Designed to handle massive datasets, scaling up to billions of records while maintaining a familiar spreadsheet interface, allowing Data Engineers to perform complex operations on large-scale data effortlessly. Self-Service Data Access, reduces dependency on Data Engineering teams for routine data queries, and empowering business users to perform basic data analytics independently. Security and Compliance: With role-based access controls, data retention policies, and SOC 2 compliance. What tool would you recommend?