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AI-Powered Data Governance & Security Platform

AI-Powered Data Governance & Security Platform

The Challenge

A leading enterprise client was facing a massive data governance challenge. They had petabytes of unstructured data (emails, documents, reports) across their organization in dozens of languages. They needed a way to automatically understand the content of every file, classify it by business category (e.g., "Finance," "Legal," "HR"), determine its confidentiality level (e.g., "Public," "Internal," "Secret"), and ensure access controls were compliant with GDPR.

Our Solution

ActiveWizards architected and built a scalable data governance platform powered by Apache Spark and advanced machine learning. Our solution provided a comprehensive, automated approach to data security and classification.


Architecture for the AI-Powered Data Governance Platform

  • Large-Scale Data Processing: We leveraged an Apache Hadoop and HBase foundation, using Apache Spark as the core processing engine. This allowed us to efficiently process massive volumes of data in parallel, handling any file type with Apache Tika for content extraction.

  • Intelligent Multilingual Classification: At the heart of the system were sophisticated machine learning models. We implemented a combination of unsupervised learning to discover hidden topics and deep learning models using Deeplearning4j and StanfordNLP. This pipeline could accurately classify documents and predict confidentiality levels in over 70 languages.

  • Real-Time Anomaly Detection: By incorporating Spark Streaming, the platform could analyze data in real-time, detecting unusual access patterns or the sudden appearance of highly confidential data in unsecured locations, triggering immediate alerts.

Key Outcomes & Business Impact

  • Automated GDPR Compliance: The platform provided an automated way to identify and protect personal and sensitive data, forming a cornerstone of the client's GDPR strategy.

  • Enhanced Data Security: By automatically correlating data classifications with user access rights, the system prevented unauthorized access to confidential information.

  • Full Data Visibility: The client gained a clear, real-time understanding of what data they had, where it was, and how sensitive it was, across their entire organization.

  • Massive Scalability: The Spark-based architecture ensured the platform could scale effortlessly to handle exponential data growth.

Technology Stack

  • Core Processing: Apache Spark, Spark Streaming, Hadoop

  • Data Storage: HBase

  • Machine Learning: Deeplearning4J, StanfordNLP

  • Content Extraction: Apache Tika

  • Frameworks: Play, Spray/Akka

  • Cluster Management: Ambari