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

BEYOND QUALITY: SECURING & GOVERNING DATA FOR ETHICAL USE A few weeks ago, I shared my experience tackling data quality issues in the oil & gas industry focusing on identifying and resolving inconsistencies, missing values, and compliance risks. But fixing data quality was only the first step. The bigger challenge was ensuring that this data remained secure, ethically shared, and regulatory compliant. As part of my project, I worked on a data-sharing scenario where an industry body required datasets to be provided to academic researchers. The issue? These datasets contained sensitive business information that couldn't be exposed carelessly. Upstream data had to align with OGA & NUPRC regulations, while corporate data needed to meet GDPR compliance to protect customer information. The risks of getting this wrong were significant: regulatory fines reaching €20M (GDPR) or £1M (OGA), potential competitive threats, and a loss of business trust due to weak governance. To address these challenges, I pseudonymized and anonymized sensitive data, ensuring that well IDs and customer records were masked while still retaining analytical value. I also encrypted files using AES-256, stored them securely with robust access controls and audit logs, and enforced Multi-Factor Authentication (MFA) and secure file transfers to prevent unauthorized access. Additionally, I drafted a Data Use Agreement (DUA) between bp and the University of Aberdeen to outline the terms for ethical and secure data usage. Working alongside my talented course mate Amarachi Grace Agiri, PMP® throughout this project has enriched the experience. Even though we were on different teams, our shared commitment to data quality and security made the experience truly enriching. This experience reinforced a crucial lesson: data quality is only as good as the security and governance surrounding it. It’s not just about accuracy, it’s about protecting and responsibly managing data in a way that ensures compliance and maintains trust. Now, I’m eager to dive deeper into enterprise-wide data governance strategies, exploring how security, compliance, and automation can be seamlessly integrated into industrial workflows. More importantly, I’m curious. How does your industry handle data security and governance? Let’s discuss! 👇 #DataQuality #DataSecurity #DataGovernance #OilAndGas #PetroleumData #GDPR #ISO27001 #Compliance #BigData #DigitalTransformation #EnergySector

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

🔐 User-Centric Credentialing & Personal Data Sharing: Rethinking Data Ownership and Digital Trust I came across a powerful concept that’s redefining how we think about data and identity, while exploring Digital Public Infrastructure (DPI) and Government Digital Transformation. That is User-Centric Credentialing & Personal Data Sharing — a vision spearheaded by Centre for Digital Public Infrastructure - CDPI and already being adopted in countries like India, Brazil, and across the EU. 📄 You can read the full vision paper here: https://vc.cdpi.dev/ 🎯 The Problem: Most of our data—academic records, financial info, medical history—sits locked in institutional silos. Whenever we need to prove something, we must go back to those institutions, again and again. This system is inefficient, exclusive, and often inaccessible to those without digital privilege. 🔄 The Shift: Instead of relying on fragile paper documents or non-verifiable PDFs, Verifiable Credentials (VCs) allow individuals to receive cryptographically signed, tamper-proof data directly from the source—and hold it themselves. Your credentials live in a digital (or even printable) wallet, ready to be presented anywhere, anytime. 🧩 Why this matters: 🚫 No more redundant verification loops or complex API integrations 💸 Individuals and SMEs can unlock low-cost, high-trust access to loans and services 🌐 Cross-border, cross-sector data sharing becomes truly scalable 🔐 Privacy-preserving tech like selective disclosure and zero-knowledge proofs lets users control what they share 💼 Real-World Use Cases: 🚜 Farmers accessing government subsidies 🎓 Students applying for global jobs or education 🛒 Micro-entrepreneurs seeking credit 🌱 Green energy prosumers trading surplus power 🔧 How it works — The Technology: ✅ Verifiable Credentials (VCs) Issued by trusted institutions (banks, hospitals, universities) Tamper-evident and cryptographically signed Verifiable without contacting the issuer Works online, offline, and across borders 🌍 Decentralized Identifiers (DIDs) Globally unique, user-owned digital identifiers Enable selective disclosure and zero-knowledge proofs Not tied to any centralized registry or country 🧠 The Architecture: Trust Without Friction 🟩 Issuer → signs and issues the credential 🟦 User → stores it in a wallet (smartphone, cloud, or paper with QR) 🟨 Verifier → verifies it cryptographically, without needing the issuer again This model eliminates the need for bilateral system integrations. Just one connection: the user. It’s asynchronous, scalable, and privacy-respecting. 🌐 Why this matters for the future: 📲 Anyone, even without advanced tech access, can participate 🛠️ Institutions issue once and never worry about re-verification 🔐 Built on open standards, decentralized architecture, and zero-trust principles Ministry of Digital Economy - Sri Lanka Information Communication Technology Agency of Sri Lanka

🚨 "I Accidentally Made Our Financial Report Public" – Don't Be That Person You've built incredible insights. Now comes the scary part: sharing them securely. One wrong click on "Publish to Web" and your confidential data becomes searchable on Google. Let's make sure that never happens to you. Why Secure Sharing Isn't Optional: Trust is fragile. One data breach, one unauthorized access, one accidental exposure – and months of credibility vanish instantly. Secure sharing isn't just IT compliance; it's career protection. 📊 Your Sharing Arsenal (Choose Wisely): 1. Direct Share: Quick email or link distribution - Best for: Small teams, single reports - Watch out: Carefully set Viewer vs Editor permissions 2. Workspaces: Collaborative environments with granular control - Best for: Ongoing projects, team collaboration - Power move: Assign Admin/Contributor/Viewer roles strategically 3. Apps: Polished packages of dashboards and reports - Best for: Large-scale stakeholder distribution - Game-changer: Users consume insights without editing chaos 4. Teams/SharePoint Integration: Seamless collaboration within existing workflows - Best for: Organizations already living in Microsoft 365 🔒 The Security Layers That Matter: - Row-Level Security (RLS): Regional managers see only their region, sales reps only their accounts – automatic personalization without building multiple reports. - Sensitivity Labels: Mark reports as "Confidential" or "Internal Only" for clear data classification. - Regular Audits: Monitor who accessed what, when. Spot unusual patterns before they become problems. ⚠️ The Critical Don'ts: ❌ Never use "Publish to Web" for anything remotely sensitive ❌ Don't give Editor access when Viewer is sufficient ❌ Avoid sharing datasets directly – share reports instead 🚀 Pro Configuration: Combine RLS + Apps + Workspaces for the ultimate secure sharing trifecta. One app per department ensures structured, controlled distribution that scales. Fast sharing is easy. Secure sharing requires strategy. The five minutes you spend setting proper permissions saves you from career-defining mistakes. The Trust Equation: Great insights + Secure delivery = Stakeholder confidence + Your reputation protected Tags : Shashank Singh 🇮🇳 | Pradeep M | Dhaval Patel | Hemanand Vadivel | Saddam Ansari | Codebasics | Indian Data Club | Munna Das | Tejas Rane | Tajamul Khan #PowerBI #DataSecurity #SecureSharing #BusinessIntelligence #DataGovernance #Compliance #Enterprise #InfoSec #DataProtection

Plant breeding generates massive datasets, but most remain locked in silos due to trust barriers and technical incompatibilities that slow innovation. Our new study introduces "Data cohorts" (structured packages of interoperable breeding data) paired with a Data Trustee Platform that enables federated sharing while protecting proprietary interests. By implementing FAIR principles from the start and using dynamic licensing with secure analysis environments, we show how genomic prediction accuracy doubled when aggregating previously isolated datasets. The key? Standardized metadata, common genotype references, and quality metrics that let breeders access relevant data without compromising competitive advantage. When data flows freely but safely, everyone's breeding programs get stronger and innovation accelerates. https://lnkd.in/dq2dJUHk

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