What is Connected Data?
Connected data offers a way to map relationships between data sources to provide context and increase the value of existing data to a business. Data siloes offer little value to a business. By connecting different data points about a subject, such as a customer, a picture can be painted to enrich interactions with the additional context. The more data points about an entity can translate into higher potential value from the relationship.
Connected Data Examples
Below are some examples of where connected data can improve a business function:
Sales
The sales team must be well-informed when interacting with prospects and customers. For prospective customers, it is advantageous to know about changes in a company as change often triggers a purchase. For example, if a customer receives a new investment to expand in a specific area, the resulting job postings and market news can uncover new projects. For existing customer relationships, it is helpful for sales to know of the customer’s open technical issues or enhancement requests.
Marketing
The marketing function is very data-driven, using internal metrics to measure success and external data to understand market and customer dynamics. Each customer journey contains milestones that follow a path to a qualified lead that can be handed to sales. Each data point from that journey, such as landing pages visited, asset downloads, keyword searched, or ad clicks, triggers an uptick in their lead score as a candidate for sales to develop. The accumulation of connected data points creates an understanding of the customer’s interests before the first meaningful conversation occurs.
Service Support
Support organizations use connected data to understand the context of every call or inbound email. The service analyst must understand the environment their product is operating within, the expected service level, the criticality of the business, past escalations, and other open cases to resolve an incident correctly. By looking across all cases to see similar issues, the problem management system can automate root cause analysis to ensure no repeats of an issue.
Account Management
An account manager can do a better job if they can look at historical trends in the relationship, monitor social media to get a feel for the sensitivities their customer may have and come to the meeting armed with the right insights to demonstrate their competency.
Engineering & Development
During the development phase, a company can only test with a subset of use cases compared with a real-world deployment. Collecting and connecting data about production use helps to reduce bugs and allows for proactive maintenance. IoT sensors can provide masses of data to be looked at holistically to understand, with context, how a system operates in the wild.
Manufacturing
Connected data enables manufacturers to make data-driven decisions and optimize supply chain management, resulting in increased efficiency and cost savings. As more manufacturers adopt connected data technologies, they will continue to benefit from improved productivity, quality, and profitability.
Product Management
Product managers regularly interact with users of their product or service to understand its strengths and identify areas for improvement in future revisions. Usage data helps to locate areas that can be retired or refactored as options. The more data points the product manager gathers about the product, the more context is gained about where to take the roadmap for maximum benefit for the vendor and customer.
Actian Makes it Easy to Analyze
Actian Data Intelligence Platform is purpose-built to help organizations unify, manage, and understand their data across hybrid environments. It brings together metadata management, governance, lineage, quality monitoring, and automation in a single platform. This enables teams to see where data comes from, how it’s used, and whether it meets internal and external requirements.
Through its centralized interface, Actian supports real-time insight into data structures and flows, making it easier to apply policies, resolve issues, and collaborate across departments. The platform also helps connect data to business context, enabling teams to use data more effectively and responsibly. Actian’s platform is designed to scale with evolving data ecosystems, supporting consistent, intelligent, and secure data use across the enterprise. Request your personalized demo.
FAQ
Connected data is an approach where data from multiple systems, applications, and sources is linked through relationships, metadata, and semantics to create a unified, context-rich view across the organization.
Connected data breaks down silos, improves data discoverability, supports accurate analytics, strengthens governance, and enables AI systems to understand how datasets relate to each other across business functions.
By linking data assets through shared entities, lineage, and metadata, connected data provides AI models and analytics engines with context that improves accuracy, relevance, and explainability in insights and predictions.
Key technologies include knowledge graphs, metadata management platforms, data catalogs, master data management (MDM), data lineage tools, semantic models, and integration frameworks that map relationships across systems.
Common use cases include customer 360 views, supply chain visibility, fraud detection, regulatory compliance, data governance, enterprise search, and retrieval-augmented generation (RAG) models that rely on contextual data relationships.
Challenges include integrating disparate systems, aligning schemas, maintaining consistent metadata, establishing governance standards, mapping lineage across complex pipelines, and ensuring the accuracy of relationships over time.
