Book: Data Engineering for Beginners
Author: Chisom Nwokwu
ISBN: 9781394325412
Chapter 8 is a wake-up call. You can build the fanciest warehouse and the cleanest pipelines, but if the data itself is garbage, none of it matters. Nwokwu makes the case that data quality is not just a technical checkbox. It is a business strategy.
In Part 1 we covered how data governance breaks into three pillars (usability, security, accountability) and went through metadata, Dataplex search, access control in BigQuery, and the Sensitive Data Protection service for finding PII. Now let’s pick up where we left off: understanding what SDP actually finds, and then moving into the accountability pillar.
Chapter 8 of Data Engineering for Beginners opens with a statement that should be obvious but apparently is not: even the best pipelines and storage systems are meaningless if the data they deliver is garbage.
You know that feeling when you buy fresh ingredients for dinner, and then spend 80% of your time washing, cutting, and peeling? The actual cooking takes 20 minutes. Data science is exactly like that. The cooking is the model. The prep work is this chapter.
Chapter 6 of Data Science Foundations by Stephen Mariadas and Ian Huke is about something that sounds boring but really is not. Properties of data. What kind of data are you working with? And why does it matter so much?