The importance of Analytics for business

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The importance of Analytics for business

Knowing how to manage and process data, information, is an asset of the digital enterprise. That’s why analytics tools are becoming increasingly important in the manufacturing sector.

As highlighted by Gartner in one of its Magic Quadrant for Analytics and Business Intelligence Platforms, the trend (as well as the differential on which industry players are playing the game) is to offer “augmented capabilities.”

Essentially, Artificial Intelligence and Machine Learning technologies are used to automate the operations of the entire data stream: from preparation, to extraction, to optimization. All these functionalities would allow to speed up the interpretation of the results, thanks to the AI suggestions.

The use of machine learning techniques must be focused to automatically provide results of interest and allow users to access them as quickly as possible.

This integration must allow users to formulate queries dedicated to their business, through fast search. By choosing a cloud deployment, the IT department can focus on core business initiatives rather than implementing and supporting multiple technologies. And with cloud-based technologies, business users can quickly access the solutions they need.

This is simplifying the way AI and machine learning are integrated into decision making: customers will no longer be constrained by programming language, data silos or specific skills. Automated data preparation, machine learning and model deployment will improve the productivity of data science resources and bring the power of artificial intelligence to non-experts.

About The Author

Before joining Alleantia in mid-2011, Antonio spent 20+ years in telecommunication networks, services and management platforms industry around the world, from coding of communication stacks in Italy and in ...