Enterprise Data Management & security Services Data governance & protection Understand, classify and safeguard your data to ensure responsible access, reduce risk and enable secure use of your information by both people & AI. Talk to Concurrency Understand, Protect & Manage Your Data Understand Your Data Gain visibility into your data landscape by locating, identifying, classifying, and organizing information so you know what data you have and how it’s being used. Protect your data Safeguard sensitive and business-critical information through robust security measures, ensuring responsible access and reducing risk for both people and AI. Manage Data Lifecycle Keep the data you need, remove the data you should. Retain only what’s necessary for business or compliance reasons and securely dispose of unnecessary or outdated data to minimize risk and optimize operations. Common Data Governance Challenges We Solve Gain Visibility into Your Data Lack of visibility into all organizational data leads to unknown risks and missed opportunities. Reduce Risk of Data Exfiltration Increased risk of data breaches or unauthorized access due to inconsistent protection and classification. Meet Data Compliance Requirements Challenges meeting compliance requirements and retention policies leads to the risk of regulatory penalties or data sprawl. Reduce Storage Costs & Data Exposure Inefficient data lifecycle management, resulting in unnecessary storage costs and exposure from retaining outdated or irrelevant data. Ready to Secure Your Data for People and AI? Let’s Talk! Data Governance & Protection Consulting Services Data Catalog & Discovery Gain visibility into what data you have, where it lives, and how it’s used. Learn More Data Classification & Endorsements Classify and label data so the right people—and AI—use it responsibly. Learn More Document-Based Data Protection Protect unstructured files wherever they live and travel. Learn More Structured Data Protection Secure sensitive data inside databases and applications. Learn More Data Lifecycle Management Keep what you need, remove what you don’t. Learn More AI Data Security Enable AI without putting your data at risk. Learn More Insider Risk Management Protect your organization from intended or unintended risks caused by your employees actions. Learn More Data Catalog & Discovery Data Classification & Endorsements Document-Based Data Protection Structured Data Protection Data Lifecycle Management AI Data Security Insider Risk Management Data Catalog & Discovery Gain visibility into what data you have, where it lives, and how it’s used. Learn More Data Classification & Endorsements Classify and label data so the right people—and AI—use it responsibly. Learn More Document-Based Data Protection Protect unstructured files wherever they live and travel. Learn More Structured Data Protection Secure sensitive data inside databases and applications. Learn More Data Lifecycle Management Keep what you need, remove what you don’t. Learn More AI Data Security Enable AI without putting your data at risk. Learn More Insider Risk Management Protect your organization from intended or unintended risks caused by your employees actions. Learn More Data Catalog A Data Catalog provides a centralized view of your organization’s data so teams can find, understand, and trust the information they use. We help organizations establish a governed data catalog that improves visibility, supports compliance, and enables responsible data use for analytics and AI. We offer a range of solutions to fit your needs: Data Discovery & Inventory: Identify and map data across cloud, on‑prem, and SaaS platforms. Metadata & Lineage: Understand where data comes from and how it flows through the organization. Governed Access: Enable discovery while maintaining security and compliance controls. Endorsements & Classification Endorsements and classification establish clarity around what data is trusted, sensitive, or restricted. We help organizations apply consistent classification and endorsement models that reduce risk, improve data quality, and enable confident data sharing across the business. We offer a range of solutions to fit your needs: Sensitivity Labeling: Define and apply labels aligned to risk and compliance requirements. Trusted Data Endorsements: Identify and promote certified and curated datasets. Policy Alignment: Enforce consistent handling of data across users, systems, and AI tools. Document‑Based Data Protection Document‑based data protection safeguards sensitive information stored in files, email, and collaboration tools. We help organizations implement controls that prevent data leakage, enforce access policies, and protect documents across Microsoft 365 and connected platforms. We offer a range of solutions to fit your needs: Information Protection: Apply encryption and access controls to sensitive documents. Data Loss Prevention (DLP): Prevent accidental or intentional data exposure. User & AI Access Controls: Ensure documents are used responsibly by people and AI. Structured Data Protection Structured data protection focuses on safeguarding sensitive information stored in databases, data platforms, and applications. We help organizations protect structured data through classification, access controls, and monitoring—reducing risk while enabling analytics and AI workloads. We offer a range of solutions to fit your needs: Data Classification: Identify sensitive fields within structured data sources. Access & Security Controls: Enforce least‑privilege access and policy‑based protection. Monitoring & Risk Detection: Detect misuse or exposure across structured datasets. Data Lifecycle Management Data lifecycle management ensures data is retained, archived, or deleted based on business and compliance needs. We help organizations reduce risk and storage costs by defining retention policies that keep critical data while eliminating unnecessary or outdated information. We offer a range of solutions to fit your needs: Retention Strategy & Policy Design: Align lifecycle rules to regulatory and business requirements. Automated Retention & Deletion: Enforce policies consistently across platforms. Compliance & Audit Readiness: Reduce exposure and support regulatory obligations. AI Data Security AI Data Security ensures sensitive information is protected as organizations adopt AI and copilots. We help define what data AI can access, apply governance and monitoring controls, and reduce the risk of oversharing or misuse—enabling responsible, secure AI adoption. We offer a range of solutions to fit your needs: AI Data Readiness: Identify which data is safe and appropriate for AI use. Access & Oversharing Controls: Prevent sensitive data exposure through AI tools. Ongoing Monitoring & Governance: Maintain visibility as AI usage evolves. Insider Risk Management Why Leading Enterprises Choose Concurrency Leading enterprises choose Concurrency because strong data governance requires clarity, consistency, and trust—not just technology. We help organizations understand their data, protect sensitive information, and manage data responsibly across its lifecycle so it can be used confidently by both people and AI, reducing risk, supporting compliance, and creating a trusted foundation that scales with the business and evolving AI initiatives. DATA GOVERNANCE & PROTECTION FREQUENTLY ASKED QUESTIONS What is data governance and why is it important for enterprises? Data governance is the practice of understanding, managing, and protecting data so it can be used responsibly and securely. For enterprises, strong data governance reduces risk, supports compliance, improves data quality, and enables trusted use of data for analytics and AI initiatives. How does data governance reduce security and compliance risk? Effective data governance reduces risk by identifying where sensitive data lives, classifying it correctly, and enforcing consistent protection and retention policies. This helps prevent data exfiltration, unauthorized access, and compliance violations while improving audit readiness and visibility across the data estate. How does data governance support AI and Copilot adoption? AI and copilots rely on access to large volumes of data, which increases the risk of oversharing or misuse. Data governance ensures only appropriate, well‑classified data is available to AI tools, enabling responsible AI adoption while protecting sensitive and regulated information. What is the difference between data protection and data governance? Data protection focuses on securing data through controls like encryption, access policies, and data loss prevention. Data governance is broader—it includes protection, but also covers discovery, classification, lifecycle management, compliance, and decision‑making around how data is used by people and AI. How do organizations gain visibility into their data? Organizations gain visibility by implementing data discovery, cataloging, and classification across structured and unstructured data sources. A governed data catalog helps teams understand what data exists, where it’s stored, who can access it, and how it’s being used. How does data lifecycle management reduce cost and risk? Data lifecycle management ensures data is retained only as long as necessary for business or regulatory purposes and securely deleted when it’s no longer needed. This reduces storage costs, limits exposure from outdated data, and helps organizations meet retention and compliance requirements. What platforms and tools support data governance and protection? Modern data governance is commonly enabled through Microsoft platforms such as Purview, Microsoft 365, Azure, and Fabric. These tools support data cataloging, classification, protection, compliance, and AI data security across cloud, on‑prem, and SaaS environments. When should an organization invest in data governance? Organizations should invest in data governance when facing compliance challenges, security incidents, AI adoption initiatives, or rapid data growth. It’s especially critical before deploying AI, copilots, or advanced analytics to ensure data is trusted, protected, and used responsibly. Case Studies 01 Accelerating AI Readiness With a Copilot Agent Enablement Day 02 Improving Inventory Visibility With a Visual Inventory Tracking System 03 Scaling Operational Efficiency With AI‑Driven Document Matching 04 Accelerating Developer Productivity With GitHub Copilot Enterprise 05 Optimizing Complex Operations With Predictive Intelligence 06 Accelerating Sales Order Processing with AI-Powered Automation 01 Accelerating AI Readiness With a Copilot Agent Enablement Day A large U.S.-based financial services organization partnered with Concurrency to accelerate hands‑on adoption of AI agents using Microsoft Copilot. While interest in Copilot was already strong, leadership wanted to move beyond experimentation and ensure teams understood how to apply Copilot and agents in a secure, practical, and business‑relevant way. Concurrency delivered an in‑person Copilot Agent Day designed to build foundational knowledge, surface real use cases, and create momentum for scalable AI adoption. View Details 02 Improving Inventory Visibility With a Visual Inventory Tracking System A U.S.-based industrial distributor partnered with Concurrency to modernize how it tracks, searches, and sells inventory across warehouse and sales teams. Operating in a resale‑driven environment where inventory changes constantly and varies by condition, the organization needed a faster, more reliable way to capture inventory details and make them immediately visible to sales. Concurrency delivered a visual, photo‑first inventory tracking system that reduced manual effort, improved response times, and established a scalable foundation for future automation. View Details 03 Scaling Operational Efficiency With AI‑Driven Document Matching A U.S.-based industrial distributor partnered with Concurrency to modernize high‑friction, document‑driven operational workflows tied to purchasing coordination and receivables processing. As transaction volume increased, leadership wanted to reduce manual effort and improve accuracy without adding headcount or replacing core systems. Through targeted automation and governance‑first design, Concurrency helped the organization establish a scalable foundation for efficient, AI‑enabled operations. View Details 04 Accelerating Developer Productivity With GitHub Copilot Enterprise A U.S.-based organization partnered with Concurrency to enable GitHub Copilot Enterprise across its development teams. As interest in AI‑assisted development increased, leadership wanted to ensure adoption delivered measurable productivity gains—not just experimentation. Through structured enablement and governance guidance, Concurrency helped the organization establish a scalable foundation for responsible, high‑impact Copilot adoption. View Details 05 Optimizing Complex Operations With Predictive Intelligence A multinational industrial organization partnered with Concurrency to improve the efficiency and consistency of a mission‑critical operational process. Because the process runs continuously at high volume, even fractional performance improvements translate into meaningful financial impact. Concurrency delivered a predictive, machine‑learning‑driven optimization solution that improved throughput, reduced variability, and established a scalable foundation for predictive operations across facilities. View Details 06 Accelerating Sales Order Processing with AI-Powered Automation A leading industrial manufacturer partnered with Concurrency to modernize its manual, error-prone sales order entry process. By implementing a scalable, AI-driven automation platform built on Microsoft Azure, Dynamics 365, and Power Platform, the organization streamlined operations, reduced labor costs, and improved customer responsiveness. Discover how a phased, value-focused approach delivered measurable ROI and laid the foundation for future AI innovation. View Details Previous Next Blog Data, KQL, Log Analytics, Microsoft, Microsoft Sentinel, Transform Transforming Log Analytics: How We Saved a Company Over $100,000 November 7, 2023 Joseph Dutton
