Difference between modern and traditional data quality
Modern data quality practices leverage advanced technologies, automation, and machine learning to handle diverse data sources, ensure real-time processing, and foster col...
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Machine learning in marketing: 10 use cases and implementation tips
Given how quickly the digital marketing industry changes, keeping up with the most recent trends and technologies can be challenging. Traditional marketing techniques are...
New Book: Statistical Optimization for GenAI and Machine Learning
In the last two years, I published 5 machine learning and AI books, including one on synthetic data by Elsevier. This represents over 800 pages of compact, state-of-the-a...
Future-proofing advanced data warehouses
Introduction Data warehouses are the linchpins of modern data infrastructure, integral for businesses that rely on informed decision-making. They act as centralized repos...
The Danger of Untethered Use Cases
Client: “We’ve identified over 60 use cases!” Schmarzo: “You might as well have zero…” I always get very concerned when I see organizations that jump right in...
Mastering data management: Efficient strategies for success
Effective data management is critical to any organization’s success in today’s data-driven world. With the exponential growth of data, businesses need to impl...
Artificial Intelligence: Making waves in the stock market
Stock trading is an industry that has greatly benefited from artificial intelligence (AI). AI algorithms in stock trading have enabled traders to make better decisions an...
Regulatory Capture: Why AI regulation favours the incumbents
We are seeing a flurry of regulation But we should ask ourselves if we are seeing regulatory capture — ie letting corporations write lax rules that lead to public...
Andrew Ng for President?
We are seeing a bunch of AI regulatory announcements from both sides of the Atlantic President Biden with his executive order on safe, secure and trustworthy ...