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Big Data, Machine Learning, Security and GRC

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With the increased variety, volume, velocity, of datas generated. Companies are growing concerns over, how to integrate “Big Datas” from sources which can be trusted and how to ensure compliance with data management, internal policies and external regulatory requirements.

A topic which has been discussed for quite sometime (see http://www.ventanaresearches.com)
Is today more actual than ever.

Machine Learning neural_networking

According to wikipedia, Machine Learning is a branch of artificial intelligence that concerns the construction and study of systems that can learn from data, it could be added that often the focus is on prediction. Machine Learning does present challenges for companies with regulatory requirements dictating Data Privacy and Data Retention.

To protect user anonymity, data should be non identifiable

Three elements to consider:

Regulatory Aspects
On one side, regulatory requirements are somehow unconnected from security requirements.

Technology
Integration with SOA, REST APIs, Cloud

Users
Adopting Innovative Technologies

And one identified path to ensure higher level of security allowing innovation: Governance, Risks and Compliance, GRC

Security is a high objective which is possible to improve, defining best practices to tackle the risks which arise with new technologies and changing economic models.

Security professionals refers to security best practices as a loop “ [that is] efficient and transparent, repeatable, [of] predictable governance [a] feedback loop…”. With focus on risks management, to achieve higher level of security in fast paced tech innovations driven times.



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