Articles

Over the last nine years, our journey at CluedIn has been dedicated to mastering data management and data quality. We’ve encountered countless challenges, learned from our customers, and seen first-hand the transformative potential of good data. So, what have we learned along the way? Here are the top insights we’ve gained from nearly a decade of building a platform designed to meet the real needs of modern businesses.

At CluedIn, we're excited to announce a refreshed website and refined messaging that reflect our deep commitment to helping businesses overcome their most pressing data management challenges. Our new site is designed to communicate CluedIn’s core mission and values more clearly than ever, and it better showcases how we are innovating in data quality, Master Data Management (MDM), and AI-enhanced data management solutions.

The modern medallion-style architecture has become the standard framework for managing data flow through various stages of transformation and enrichment, typically organized as Bronze, Silver, and Gold zones. Each stage serves its own purpose: Bronze for raw data, Silver for cleansed data, and Gold for highly refined, analytics-ready data.

In recent years, artificial intelligence has significantly impacted data management, but we’re on the cusp of something even bigger: AI agents transforming how data teams operate. Unlike traditional automation, which often handles repetitive tasks, AI agents bring a new level of intelligence and collaboration. They’ll be pivotal in shaping how data is managed, governed, and utilized, providing unique advantages that extend beyond mere efficiency.

In the era of sustainability and social responsibility, organizations are increasingly focusing on Environmental, Social, and Governance (ESG) initiatives. These initiatives not only demonstrate a commitment to ethical practices but also offer a pathway to long-term value creation. However, to effectively manage ESG strategies, accurate, consistent, and comprehensive data is crucial. This is where Master Data Management (MDM) plays a transformative role, serving as the backbone for successful ESG initiatives.

Today, we announced a powerful suite of updates to CluedIn, designed to make data management more seamless, efficient, and intelligent for business users. Our latest offerings bring AI-powered insights and continuous data quality management right to your fingertips, helping organizations stay agile and efficient in an increasingly data-intensive landscape. 

We’re proud to introduce a series of powerful new features and integrations between CluedIn, Microsoft Fabric, and Microsoft Purview, designed to help organizations unite business and technical teams as they realize value from across their data estate. From exporting data to target Fabric applications and real-time data lineage in Purview, here’s how CluedIn is enhancing the way you manage data in the Microsoft ecosystem.

CluedIn and Telefónica Tech announce new partnership to accelerate data-driven value for Microsoft customers

Introduction

In the world of traditional data management, reference data and master data are treated as two different categories of data. Reference data is used to classify or categorize other data, and master data is business-critical data shared by multiple systems, applications, and processes. Conventionally, examples of master data include customer data, product records, and vendor data. Reference data includes code lists, taxonomies, and hierarchies of data, amongst other things.

Introduction

Believe it or not, the structure of your MDM system can dramatically affect your organization's ability to derive insights and value from data. Traditional Master Data Management (MDM) systems are built using relational databases, whereas more modern platforms utilize Graph. With their superior handling of interconnected data, graph-based systems offer distinct advantages in several key scenarios over traditional relational databases.