Tag: data privacy

India, Risk & Fraud Management

Insights from Gartner Risk & Security Summit 2025: What You Need to Know

By Bidya Bhushan Bibhu | March 2025 I recently attended the Gartner Risk and Security Summit 2025, and the experience was eye-opening. Gartner experts and industry leaders gathered to discuss the future of security, risk management, and compliance, highlighting critical changes and trends impacting businesses globally. If you’re someone who thinks risk management is only for technical teams, think again. The conference clearly showed how … Continue reading Insights from Gartner Risk & Security Summit 2025: What You Need to Know

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Data

Privacy-Preserving Data Analytics: The Future of Secure AI, Compliance, and Innovation

Overview Data privacy is becoming an increasingly critical aspect of analytics and machine learning. Organizations face challenges balancing data utility and privacy, especially with strict regulatory requirements such as GDPR and CCPA. In response, companies like Google have pioneered advanced privacy-preserving techniques, such as federated learning and differential privacy, which enable robust data insights while maintaining privacy. Let’s explore these methods and how they redefine … Continue reading Privacy-Preserving Data Analytics: The Future of Secure AI, Compliance, and Innovation

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Data, Data Products & Innovations

How Microsoft Enhances ML with Synthetic Data Techniques

Unlocking Synthetic Data: Microsoft’s Path to Privacy-Preserving ML The rise of synthetic data generation marks a pivotal shift in how machine learning (ML) models are trained, especially in sensitive fields like healthcare. By creating data that mimics the properties of real datasets, synthetic data enables organizations to train models without exposing sensitive information. Microsoft has been at the forefront of this innovation, exploring its use … Continue reading How Microsoft Enhances ML with Synthetic Data Techniques

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Data, Data Products & Innovations

Mastering Data Observability for ML Success at LinkedIn

Ensuring Reliable ML Pipelines with DataHub What to Expect in the Blog?Explore LinkedIn’s approach to data observability and metadata management with DataHub, focusing on proactive monitoring, data lineage, and data quality enhancement across ML pipelines. Tags: LinkedIn, DataHub, data observability, metadata management, ML pipeline reliability, data lineage, data quality, proactive monitoring Data Observability at LinkedIn Keeping ML Pipelines Reliable with DataHub Maintaining reliable machine learning … Continue reading Mastering Data Observability for ML Success at LinkedIn

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Data

Federated Learning: A Privacy-Preserving Approach to AI

Data privacy is becoming an increasingly critical aspect of analytics and machine learning. Organizations face challenges balancing data utility and privacy, especially with strict regulatory requirements such as GDPR and CCPA. In response, companies like Google have pioneered advanced privacy-preserving techniques, such as federated learning and differential privacy, which enable robust data insights while maintaining privacy. Let’s explore these methods and how they redefine data … Continue reading Federated Learning: A Privacy-Preserving Approach to AI

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