5 Best Practices to Build Trusted Data Products

Organizations prioritizing data aim to cultivate a culture of using high-quality, reliable data and trusted analytics for informed decision-making, viewing data as a product to gain insights, automate processes, and enhance customer experiences. The shift towards treating data as a product is evident in industries like ride-hailing and delivery, where data-driven operations have disrupted traditional business models. To build effective data products, companies are encouraged to adopt best practices such as employing strong data engineering techniques like documentation and testing, establishing robust data processes to manage changes, empowering all team members to manage data, ensuring alignment between data producers and consumers, and promoting transparency in data reliability issues. Soda, an open-source package, supports these practices by offering tools to measure data attributes, formalize controls, and maintain transparency, ultimately helping data teams design and manage data products more efficiently.