While some companies may experience data incidents on a daily basis, others may go days – if not weeks – without one. The criticality of the incidents can vary from something “minor,” such as stale data linked to a dashboard that nobody has used in ages, to a data duplication problem causing the server to overcharge and ultimately go hong kong whatsapp number data down (true story, Netflix 2016). We find it is often linked to: the size and complexity of the data platform, the company’s industry (some industries are inherently more data mature than others), data architecture type (centralized, decentralized, hybrid), etc. Documenting the incidents will give a better idea of what to look for next time there is one, repeated incidents are often a good indicator that something underneath needs closer attention.
Incident classification: Not all data incidents are of the same severity; some may be minor and easily mitigated, while others can have serious consequences. Documenting the criticality of the incidents is important to ensure proper escalation and prioritization.
This is where data lineage can be instrumental, as it allows the assessment of the downstream impact of the incident to better understand the criticality. An incident that is linked to the CEO’s favorite dashboard, or a production database, or an important data product is likely to be of high criticality.