> For the complete documentation index, see [llms.txt](https://docs.eseye.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.eseye.com/api-reference/connectivity-metrics/correlate-the-datasets.md). # Correlate the datasets The three datasets (authentication, accounting and traffic flow) can be used together to provide a complete view of a device’s connectivity activity or separately to answer specific operational questions. #### Correlation keys You can typically correlate records using **IMSI and timestamp**. The IMSI identifies the SIM across all three datasets, while the timestamp aligns records within the same period of activity. #### How the records connect The three datasets describe consecutive stages of a device’s connectivity activity: 1. Review **authentication records** to confirm whether the device attached successfully and identify rejected attempts or repeated reconnects. 2. Review **accounting records** to determine whether a session was established, how long it remained active and how much data it transferred. 3. Review **traffic flow (NetFlow) records** to identify where the data went while the session was active. For example, repeated authentication rejections, short accounting sessions and few traffic flow records may indicate an unstable connection. A successful attachment, a long session and heavy traffic to an unexpected destination may point to a different issue. Correlating the datasets makes these patterns easier to distinguish. #### Example investigation Consider a device reported as consuming more data than expected. Accounting records confirm the amount of data consumed and show when the relevant sessions occurred. Authentication records for the same IMSI and time period show whether the device was reconnecting repeatedly, which may indicate instability rather than expected usage. Traffic flow records then identify the destinations that received the data, helping you distinguish expected application traffic from unexpected communication. Together, the records provide a complete, time-aligned view of the device’s connectivity behaviour. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.eseye.com/api-reference/connectivity-metrics/correlate-the-datasets.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.