Data optimization is the process of ensuring you are extracting the most value from your data at every stage of its journey, from capture, storage, maintenance and security, to its analysis and insights, and finally its archiving and deletion.
But if that’s what it is, what does it entail and require? It sounds like an enormous amount of work and potential upheaval, so to help, we have broken it down into 12 of the most important steps.
Data privacy laws are complex, widespread and evolving. From Europe’s GDPR to California’s new privacy legislation, CCPA, as well as industry-specific regulations, it’s essential to identify which frameworks you must adhere to, plus any that may become applicable as your future strategy evolves.
Is what you want to achieve with your data ethical? This is a question of more than whether it is line with the regulations (see the previous point), but is it in line with their underlying sentiment and purpose? Where does your project sit on the spectrum of using data to deliver services, insights and capabilities that are genuinely equally beneficial to them and you, versus exploiting their data and privacy (and potentially legal loopholes) to largely your ends?
Have your projects, processes and core activities been built with privacy in mind? Privacy by Design helps businesses be proactive when it comes to data privacy, ensuring it’s planned into the project from the very start, and in such a way that privacy does not hinder any ambition or objectives. If privacy is an afterthought and implemented retrospectively, then it will invariably restrict functionality and diminish the project’s effectiveness. Privacy should never be an obstacle to progress, only a safeguard to ensure that progress is ethical.