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Responsible Gaming in the Age of Machine Learning

BizAcuity

Only, the data required to do this is not so easily available. Rooted in a comprehensive and proactive approach to real-time data analytics we aggregated player lifetime and frequency metrics and computed them to predict and analyse problem gaming behaviours or trends in players. That too, efficiently.

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Embedded Analytics: Should you build or buy?

Tableau

1 Timely, accurate, dynamic data that’s easy to use . Before AmFam had Embedded Analytics, real-time data and reports were not readily available to agents. Instead, they saw occasional reports from their managers at select times of the year.

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What is Tableau Einstein?

Tableau

Tableau Semantics enrich analytics data for trusted insights It’s difficult to ensure that insights are based on a complete and accurate view of information. This not only creates doubt, but also makes it challenging to turn data into real business value.

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Embedded Analytics: Should you build or buy?

Tableau

1 Timely, accurate, dynamic data that’s easy to use . Before AmFam had Embedded Analytics, real-time data and reports were not readily available to agents. Instead, they saw occasional reports from their managers at select times of the year.

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The 10 Best Airbyte Alternatives In 2024

Astera

Generative AI Support: Airbyte provides access to LLM frameworks and supports vector data to power generative AI applications. Real-time Data Replication: Airbyte supports both full refresh and incremental data synchronization. Custom Data Transformations: Users can create custom transformations through DBT or SQL.

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What is Streaming ETL?

Astera

Streaming ETL is a modern approach to extracting, transforming, and loading (ETL) that processes and moves data from source to destination in real-time. It relies on real-time data pipelines that process events as they occur. Events refer to various individual pieces of information within the data stream.

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3 data trends that will drive the future of healthcare

Tableau

As on-person and at-home medical devices develop at warp speed, real-time data will also grow at an exponential pace. More medical device data requires robust data and analytics systems to ingest, cleanse and validate the data. CW : Retrospective data analysis isn't sufficient.