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Data privacy examples

IBM Big Data Hub

An online retailer always gets users’ explicit consent before sharing customer data with its partners. A navigation app anonymizes activity data before analyzing it for travel trends. One cannot overstate the importance of data privacy for businesses today. The user can accept or reject each use of their data individually.

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erwin’s Predictions for 2021: Data Relevance Shines at the End of the Tunnel

erwin

Our predictions for 2021 are rooted in what we’ve learned from the past year and the relevance of data in getting us to where we are and where we need to go. Historically, moving legacy data to the cloud hasn’t been easy or fast. However, that definition is too narrow in terms of AI’s relation to data governance.

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4 ways AI and Blockchain Transform Information Governance

Everteam

In this session, we explored AI and Blockchain’s impact on core information governance processes and records management practices. Below are 4 key takeaways from the conversation: EC M is moving toward federated information governance. AI and Blockchain extend the reach of Information Governance.

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Guest Post -- New Global Data  and Privacy Regulations in 2018 and the GDPR

AIIM

Data privacy breaches have been in the news again and again this year, eliciting increased concern from regulators and legislative bodies. But one of the most important data privacy milestones on the horizon in 2018 has its roots far earlier, and has been of utmost concern to multinational organizations. But more on them later.

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Data integrity vs. data quality: Is there a difference?

IBM Big Data Hub

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

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Best Facial Recognition Software for Enterprises In 2022

eSecurity Planet

Facial recognition software (FRS) is a biometric tool that uses artificial intelligence (AI) and machine learning (ML) to scan human facial features to produce a code. With all the gathered data on facial recognition technology, it indeed offers significant potential for the security aspects of enterprises. Amazon Rekognition.

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Kelly Twigger of ESI Attorneys: eDiscovery Trends 2018

eDiscovery Daily

The show had less focus on eDiscovery this year – and I attribute that to three things: the consolidation of service providers in the space, the perceived maturity of the eDiscovery market (it’s not), and the development of new areas of risk in legal that are sexy – artificial intelligence, blockchain, etc. Microsoft Corp.