O’Reilly x Anomalo: Use AI to Modernize Your Data Quality Strategy

The type of AI that’s getting most of the attention these days is trying to make computers act like humans. When it comes to data quality, you want computers to act like computers, working with singular focus to find specific kinds of problems.

It’s such a time- and resource-intensive topic that we wrote a book on it: O’Reilly’s Automating Data Quality Monitoring. If you’ve got the time, please read it right now, with our compliments. Otherwise, you can follow us over the coming months as we unpack practical lessons and technical best practices over 221 pages. 

You’ll get all the highlights in lessons adapted for the modern tech leader’s attention span. Just like Anomalo’s notifications, fine-tuned to tell you no more and no less than you need to know, this series will share carefully selected concepts that form the foundation of a proactive, rather than reactive, data quality strategy.

Follow along here on the Anomalo blog or on LinkedIn. You’ll also get supplementary insights from Anomallamas (that’s what we call ourselves!) with every release.

We’ll follow each of the eight chapters of the book in order:

1. The Data Quality Imperative

2. Data Quality Monitoring Strategies and the Role of Automation

3. Assessing the Business Impact of Automated Data Quality Monitoring

4. Automating Data Quality Monitoring with Machine Learning

5. Building a Model That Works on Real-World Data

6. Implementing Notifications While Avoiding Alert Fatigue

7. Integrating Monitoring with Data Tools and Systems

8. Operating your Solution at Scale

If you just can’t wait, by all means, go ahead and download the eBook, on us. Otherwise, stay tuned. We’ve got your cheat code for expert-level data quality automation coming soon!