Titlebook: Enabling Real-Time Business Intelligence; International Worksh Malu Castellanos,Umeshwar Dayal,Nesime Tatbul Conference proceedings 2015 Sp

heterogeneous

Building Engines and Platforms for the Big Data Age, insights from the data. The results of these insights are periodically deployed into the real-time pipeline, in order to perform business actions or raise alerts. We are currently witnessing a move towards ., where some of the offline activities may be performed in memory, directly over the real-ti

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Backtrack-Based and Window-Oriented Optimistic Failure Recovery in Distributed Stream Processing,tency overhead must be minimized for accommodating real-time analytics. This issue has been studied in various contexts. In this work we develop the .. mechanism to allow a task to roll forward without waiting for acknowledgement from its downstream target tasks in the failure-free case, but to requ

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LinkViews: An Integration Framework for Relational and Stream Systems,rs), social networks (status updates) and many others. While data stream management systems (DSMS) are technologically mature, they lack standardization in terms of modeling, querying and interoperability. In addition, so far, stream processing was confined within an organization. However, modern ap

apiary

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Detecting the Temporal Context of Queries,onstructed in exacting detail, assumptions about the data made during extraction, transformation, and schema and query creation of the reporting database may be (accidentally) ignored by end users, or may change as the database evolves over time. As these assumptions are typically implicit (e.g., as

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