Data

Calling data engineering a cost center is outdated. In today’s world, without high quality data, you simply cannot stay competitive. This has become even more apparent with the rise of data hungry AI companies, where data essentially is the business. I define data engineering as preparing and transforming data from any source into a useful form for a business purpose including but not limited to analysis, reporting, monetization, product development, marketing, and decision making....

This draft outlines principles and guidelines for responsible data monetization. It is intended to serve as a reference point for organizations looking to monetize data in ethical, transparent, and compliant ways. This is not legal advice, and organizations should consult with legal and compliance experts to ensure that their data monetization practices are in line with local laws and regulations. This field is rapidly evolving. Responsible data monetization has the potential to unlock medical breakthroughs, support sustainable practices, improve access in underserved communities, drive economic growth and a lot more....