With the rise in machine learning and artificial intelligence approaches to big data, systems that can integrate into the complex ecosystem typically found within large enterprises are increasingly important.
Hadoop systems can hold billions of data objects but suffer from the common problem that such objects can be hard or organise due to a lack of descriptive meta-data. SciBite can improve the discoverability of this vast resource by unlocking the knowledge held in unstructured text to power next-generation analytics and insight.
Here we describe how the combination of Hadoop and SciBite brings significant value to large-scale processing projects.
To learn more, download the full use case.
In this post we explore how SciBite's semantic platform fits into these infrastructures and how it can be used to unlock the knowledge held in text form within an organisation to power next-generation analytics and insight.Read
Over the 50 years how we collect and play music has changed dramatically from physical copies on Vinyl through to electronic mp3s. Each new technology often requires a new device and format to play yet it is still essentially just music.Read
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