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Continuous digital transformation has created a data explosion that's overwhelming many organisations. Every tap, click, or swipe from a user, new code deployment or architecture change, and attempted cyberattack generates more data that can be captured and analysed. However, there is too much data to store and use cost-effectively. Organizations are therefore forced to discard most data or lock it away in cheaper storage layers where it can't be analyzed. This has led to a tipping point, where the datasets used for observability and security analytics are too incomplete to be truly valuable. The value of observability and security data is in the insights it can provide to help organizations optimize their digital services. However, current approaches to analytics mean they often need help to maximize the detail those insights contain. As well as having an incomplete dataset, most of what they keep is stored and analyzed in silos, so it lacks a crucial ingredient – context. This means any answers from data an