Building an online datahub with Spark

Organisations demand accurate, timely, high quality data on which to base their

decisions. Building an effective, online data hub to facilitate access to this data

means ensuring solution scalability and reliability. It also means building for data

trustworthiness.

This paper addresses the value, use cases and challenges associated with building

an enterprise data hub – whether on the public cloud or on-premise – based on

Apache Spark.

Why Apache Spark for your Datahub

Apache Spark is an open source software development framework and runtime

that helps users develop parallel, distributed data processing and machine

learning applications to run at scale. Spark combines capabilities for in-memory

distributed, grid data processing with the ability to spill intermediary datasets to

disk if required.

In this whitepaper, we cover:

The value and promise of a data hub
Common data hub use cases
Challenges to adoption
An introduction to Apache Spark
How Spark helps solve data challenges
Planning a Spark implementation
Building a cloud data hub
Building an on-premise data hub

Further reading:

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