Secure Data Sharing Solutions

I’ve seen organizations trying to share sensitive intelligence using clear text or hashed data, assuming it’s “good enough.” No, it’s not! Hashes are not acceptable anymore. They can be reversed, brute forced, or cross referenced until PII leaks through the cracks. And once that happens, the damage is done. That’s exactly why we built Group-IB’s patented Distributed Tokenization technology. Instead of hashing, we completely transform sensitive identifiers into irreversible tokens—no recovery, no guessing, no exposure. And still, within milliseconds, institutions can match these tokens across the network to see if others have flagged the same device, account, or customer. This isn’t just a technical upgrade. It’s what makes real #collective #defence possible. When organizations can safely correlate threats without revealing data, everyone becomes stronger. Fraudsters lose their hiding places, and the network gains shared situational awareness in real time. I’m proud that this approach isn’t just powerful. It’s compliant. Our tokenization was independently reviewed by Bureau Veritas Group for technical design and #GDPR alignment, confirming it supports strict principles like data minimisation and pseudonymisation. If you’re still relying on hashes, you’re taking an avoidable risk. Distributed Tokenization is how you share fraud intelligence safely, in real time, without ever putting sensitive data on the line. Banks, fintechs, telcos, e-commerce, government—everyone fighting fraud—deserves a way to collaborate without compromising privacy. Want to know more? https://lnkd.in/gH4mgHzF

Safeguarding information while enabling collaboration requires methods that respect privacy, ensure accuracy, and sustain trust. Privacy-Enhancing Technologies create conditions where data becomes useful without being exposed, aligning innovation with responsibility. When companies exchange sensitive information, the tension between insight and confidentiality becomes evident. Cryptographic PETs apply advanced encryption that allows data to be analyzed securely, while distributed approaches such as federated learning ensure that knowledge can be shared without revealing raw information. The practical benefits are visible in sectors such as banking, healthcare, supply chains, and retail, where secure sharing strengthens operational efficiency and trust. At the same time, adoption requires balancing privacy, accuracy, performance, and costs, which makes strategic choices essential. A thoughtful approach begins with mapping sensitive data, selecting the appropriate PETs, and aligning them with governance and compliance frameworks. This is where technological innovation meets organizational responsibility, creating the foundation for trusted collaboration. #PrivacyEnhancingTechnologies #DataSharing #DigitalTrust #Cybersecurity

The moment you export, you lose governance. Snowflake fixed that. Most “data sharing” still looks the same. A provider exports files, the consumer loads a copy, and governance disappears the second that hand-off happens. Version chaos, missing audits, broken permissions and everyone accepts it as normal. Snowflake changed that. With Secure Zero-ETL Sharing for open table formats, sharing moves from a hand-off to a governed runtime. You can share Apache Iceberg or Delta Lake tables stored in your cloud or external catalog, and consumers query them directly across clouds and regions. The Horizon Catalog keeps control in place like masking, RBAC, audit, and lineage travel automatically. Cross-cloud auto-fulfillment and egress optimization make it efficient and predictable. You’re not exporting data anymore. You’re exposing governed endpoints that stay under your control. Databricks is heading in the same direction with Delta Sharing and Lakehouse Federation, but the experience still takes more assembly. Providers set up credentials, manage paths, and often materialize data into object storage. Consumers still handle schema alignment, endpoints, and metadata sync. Databricks gives you the parts. Snowflake gives you the product. When you share data across dozens of domains or partners, the real cost isn’t compute or storage, it’s the sharing tax: pipelines, permission lists, version tracking, and governance you have to rebuild each time. If sharing is a product, it becomes part of your platform. If it’s a hand-off, it stays a side project. Snowflake’s model lets you define policies once, and the runtime enforces them everywhere. Everything else means more scripts, more ops, and more hoping you didn’t miss something. #Snowflake #DataSharing #ZeroETL #DataGovernance #DataArchitecture #OpenFormats #Iceberg #CloudAnalytics #ModernDataStack #PlatformEngineering

Here’s the security dilemma many teams face: we block file sharing in external Teams chats to protect data, and within a week users are emailing attachments to get work done. The data leaves our tenant forever. We've traded a controlled risk for an uncontrolled one. This is a fundamental security challenge: the gap between what policy intends and what people actually do when policy gets in the way. That's why I'm excited about what we just shipped at eSHARE. Trusted Sharing for Microsoft Teams Chat lets users paste an M365 link into any Teams chat with external participants, and eSHARE instantly wraps it in a Trusted Share. The file never leaves our tenant. Access governance is enforced automatically. And the user never leaves their flow of work. No new app. No extra steps. No reason to fall back to email. Below is a quick demo showing how it works. What I love about this from a trust and governance standpoint: it doesn't ask users to choose between doing their job and following policy. It removes that choice entirely. IT gets to say yes to external collaboration in Teams without compromising on control. Guardrails, not barriers. That's the philosophy. This is what it looks like in practice. #TrustedCollaboration #MicrosoftTeams #DataGovernance #ExternalCollaboration #ZeroTrust

🚀 Delta Sharing: The Open Protocol for Secure Data Exchange Traditionally, data sharing involved providing static CSV/Parquet file dumps based on ad-hoc requests, requiring data engineers to create extracts or build complex ETL pipelines. By the time data reached recipients, it was often outdated. Additionally, moving data across organizational boundaries increased security risks and required manual auditing as well. Delta Sharing, an open protocol, solves these challenges by enabling direct, real-time data exchange while ensuring security and governance. 🔍 What is Delta Sharing? Delta Sharing is an open-source protocol that allows data providers to securely share live data from their data lake or lakehouse with any recipient, regardless of the computing platform they use. It is designed to work with Delta Lake, but it also supports other formats like Apache Parquet. 🔧 What Problems Does Delta Sharing Solve? ✅ Eliminates Data Copies – Consumers can query shared data without duplicating or exporting it into another system. ✅ Interoperability – Enables cross-platform sharing across different cloud and analytics services, including Databricks, Apache Spark, Pandas, and others. ✅ Real-time & Secure Access – Uses fine-grained access control to ensure only authorized users can access the latest version of shared data. ✅ Simplified Data Collaboration – Reduces the need for custom APIs, FTP transfers, or complex ETL workflows when sharing data with external partners. 🛠 Key Components in a Delta Sharing Scenario - Provider (Data Owner) – The entity sharing the data. - Delta Sharing Server – Handles authentication and access control. - Recipient (Data Consumer) – The entity accessing the shared data, which can be a data warehouse, a machine learning model, or a BI tool. - Storage Backend – Typically an object store (AWS S3, Azure Blob, Google Cloud Storage, MinIO) where the data resides. 📌 Common Use Cases for Delta Sharing 💡 Inter-company Data Exchange – Share supply chain, financial, or operational data with partners securely. 📊 Federated Analytics – Analysts can query live shared datasets without moving them into their own data warehouse. 🤖 Machine Learning & AI – Data scientists can directly access fresh, live data for model training without worrying about outdated extracts. ⚡ Data Monetization – Organizations can offer secure access to valuable datasets as a service without needing data pipelines. Delta Sharing + Unity Catalog Delta Sharing and Unity Catalog work together to enable secure, scalable, and governed data sharing across organizations. While Delta Sharing provides the protocol for sharing live data with external consumers, Unity Catalog acts as the central governance layer, ensuring fine-grained access control, auditing, and security compliance. I will write about this integration in the future. #deltasharing #datagovernance #datasharing

Databricks Tip of the Day: Secure Data Sharing with Delta Sharing 🔐 Share live data across organizations without copying or moving files 🎯 Recipients get read-only access with automatic updates as data changes 📊 Works with any client supporting Delta Sharing protocol (Spark, pandas, etc) ⚠️ Granular control with partition-level sharing for sensitive data Delta Sharing solves the common problem of securely sharing data between organizations or teams. Instead of copying data to S3 buckets or setting up complex cross-account access, you create a share and grant access to specific recipients. The data stays in your account, and recipients get live read-only access that automatically reflects updates. You can even share specific partitions if you only want to expose a subset of your data. This becomes really useful for partner integrations, or just sharing datasets across business units without duplicating storage or worrying about data getting stale. Docs - https://lnkd.in/dBs_rJTS #Databricks #DeltaSharing #DataSharing

With data creation projected to reach 180 zettabytes by 2025 (IDC), industries need more than just cloud storage—they need decentralized solutions. Let’s dive into how Web3 companies are transforming sectors like Healthcare, Finance, Media, Legal, Tech, and Energy with DFS.👇 🔑 6 Industries Revolutionized by Distributed File Storage: 1. Healthcare  Challenge: Securing sensitive patient data while maintaining compliance (e.g., HIPAA). Key Players: - Storj: Encrypts and distributes patient records globally for secure, compliant storage. - Internxt: Offers zero-knowledge file storage for maximum data privacy. - MedRec: Blockchain-based electronic medical record management ensuring data integrity. 2. Finance  Challenge: Protecting financial data from breaches while ensuring transparency. Key Players: - Filecoin Foundation: Provides secure, decentralized storage for transaction records and financial documents. - 0Chain: Offers GDPR-compliant decentralized storage for financial institutions. - Sia: Low-cost, secure data storage for startups and fintechs needing scalability. 3. Media & Entertainment  Challenge: Managing large media files securely while ensuring content authenticity. Key Players: - Arweave: Permanent storage for media archives and digital art, ideal for NFTs. - Pinata: Media management for NFTs and digital creators ensuring secure asset storage. 4. Legal & Compliance  Challenge: Ensuring legal documents are immutable, tamper-proof, and easily accessible. Key Players: - Arweave: Immutable, long-term storage for legal contracts and compliance documents. - Opacity: Anonymous, secure storage for sensitive legal documents. - Follow My Vote: Uses blockchain for secure, transparent digital voting systems. 5. Technology & Startups  Challenge: Affordable, scalable data storage solutions for growing businesses. Key Players: - Sia: Budget-friendly decentralized storage for startups scaling rapidly. - Filebase: S3-compatible decentralized storage, easy for developers to integrate. - Decentralized Cloud Foundation (Crust Network): Provides storage solutions for dApps and Web3 developers. 6. Energy & Sustainability Challenge: Managing and sharing energy consumption data securely in decentralized grids. Key Players: - LO3 Energy: Decentralized energy transactions via blockchain for microgrids. - Grid+: Direct-to-consumer energy trading with secure data sharing. - Safe Network (MaidSafe): Privacy-focused decentralized data storage for IoT in energy systems. Companies embracing DFS today are future-proofing their operations and ensuring data integrity in an increasingly decentralized world. Is your business leveraging decentralized storage to stay ahead? Drop a comment or DM me to explore how these solutions can transform your industry and protect your data in 2025 and beyond. 🌍🚀 #Web3 #DistributedStorage #Filecoin #Arweave #Storj #Decentralization #DataSecurity #BlockchainInnovation #FutureOfData #TechLeadership