Raising the Level of Abstraction for Time-State Analytics With the Timeline Framework

Conviva Research on Time-State Analytics
Presented at CIDR 2023

With the the time and state of streaming metrics constantly evolving, traditional models and simple aggregation queries have proven too slow, expensive and imprecise to keep up. The Conviva streaming analytics model is built on timelines not tables with a focus on continuous measurement, context-sensitive computation, and real-time diagnostics root cause attribution and data interaction. Conviva’s timeline approach improves development time, increases performance, and lowers cost. Time-State Analytics has already transformed streaming media measurement and is applicable across many more industries, in any field where context-dependent queries are important.

Raising the Level of Abstraction for Time-State Analytics With the Timeline Framework, was peer-reviewed by an expert committee of big data and computer processing experts and presented by Conviva at CIDR 2023. CIDR, the 2023 Conference on Innovative Data Systems Research in Amsterdam is the premier event in the data systems community, bringing together academics and practitioners to inform the next frontier of data processing.

Conviva’s CIDR paper was co-authored by Henry Milner (Conviva), Yihua Cheng (Conviva), Jibin Zhan (Conviva), Hui Zhang (Conviva), Vyas Sekar (Conviva), Junchen Jiang (University of Chicago), and Ion Stoica (Databricks, Conviva).

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