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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.Extract from article by Abdul Razack
Automation of data management can be transformational in the enterprise. Eliminating low-level manual processes frees up people resources, amplifying human potential to deliver more value and creativity further up the value chain.
Automation helps companies analyze data — and spot anomalies with greater accuracy and at a faster rate — in real time. Combined with machine learning, automation can grow and adapt, refining itself to deliver further efficiencies and insights.
However, automation doesn’t happen by itself. Data sources needs to drive automation. That invariably means breaking data out of existing silos so it can be fed into an automation engine, providing the engine with a complete view of the entire relevant data pile, rather than just a segment or snapshot.
Read the complete article at Big Data Analytics Success Depends on These 3 Ingredients