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Recent Success With Databricks

Over the last 6 months, we’ve been working with Databricks for a client project.  For those who aren’t aware, Databricks is a SaaS/managed version of Spark, the popular open source big data processing framework. Though we were initially sceptical about Databricks and leaned more towards DIY Spark, we had a very good experience and have now moved

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Materialised Views On Event Streams

Imagine we have a stream of events representing new orders: Much of the move to event driven architecture is about responding to these individual events and building analytics over them in order to improve time to insight and make the business more responsive. However, there will always be much more traditional requirements that we might

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Deriving Real Time Events From Legacy Systems

As we know, a lot of business intelligence and data processing within enterprises is batch based, where periodically (e.g. daily) we exchange and process large volumes of data in batches of multiple records. Fundamentally, businesses are looking to speed this up in order to use data for operational purposes, to reduce time to insight, or

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Using Real Time Data To Guide Employee Next Best Action

There has been a long held concern as to whether “Artificial Intelligence” will ultimately, replace humans en masse in the workforce. For now, this hasn’t happened, with relatively few organisations outside of Silicon Valley technology companies bringing AI & ML solutions into production, let alone to the extent they can replace large swathes of employees.

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