Where Did That Data Come From?

These inconsistencies are more common than most facility managers would like to admit. In a world increasingly reliant on real-time data for decision-making, automation and compliance, such confusion carries real cost.

This leads to a simple but powerful question:

Where did that data come from? And more importantly, can it be trusted?

The answer lies in a discipline called data lineage — a way to trace the journey of each data point, from its origin to its final destination, through every system and transformation along the way. Understanding data lineage does not require a degree in data science. But for facility professionals who manage complex environments filled with smart systems and connected technologies, it is becoming essential knowledge.

FMs must understand what data lineage is, why it matters in facility operations and how building awareness of this concept can help them troubleshoot issues, build trust in their systems and better collaborate with technical teams.

What is data lineage & why it matters

At its core, data lineage is a map. It shows where a piece of data came from, what changed it along the way and where it ended up. Think of it like tracing the ingredients in a meal: to evaluate the final product, it is important to know what went in, who handled it and how it was prepared.

In the FM context, this “meal” might be a monthly energy report, a fault alert in the building automation system or an asset record in the CMMS. Data lineage helps FMs and their organizations answer four key questions:

• Can we trust this data?

• Do we know how it got here?

• Are we confident it is compliant?

• Are the systems that use this data properly governed?

Data confidence is foundational to operational success. If technicians or managers are unsure whether a value is accurate, they either waste time verifying it — or worse, act on incorrect information.

Regulatory compliance also depends on lineage. Standards like ISO 19650 and ASHRAE 233P increasingly expect traceable, auditable records, especially for systems that affect safety, health or environmental performance.

Perhaps most critically, data lineage supports broader data governance and data management practices. In many organizations, lineage tools are part of formal data governance programs. These platforms help ensure that the right data is delivered to the right systems and that changes are traceable over time.

FM’s real-world challenges without lineage

When data lineage is missing or unclear, facility teams are left with guesswork. The consequences can be subtle at first, but cumulative over time:

• A rooftop unit in the CMMS references the wrong drawing in the BIM model, so part replacements are delayed.
• A sensor triggers false alarms because its calibration record was lost during handover.
• Space occupancy dashboards report incorrect values because room assignments were not updated across systems.

Without lineage, each system exists in isolation. Equipment IDs differ across drawings, models and maintenance logs. Sensor data flows into dashboards without clear attribution. Reports surface inconsistencies, but no one can trace where the discrepancy started.

These issues erode trust in the very systems designed to improve efficiency. And they leave facility professionals chasing ghosts — spending more time validating data than acting on it.

Anatomy of data lineage

To understand how data lineage works, consider the life cycle of data in three simple stages:

1. Source

This is where the data is created. It could be a design model authored by an engineer, a nameplate entered during commissioning or a sensor reading captured every few seconds by the building automation system.

2. Transformation

As data moves between systems, it often changes format or meaning. A model element might become an asset record. A sensor name might be translated into a standardized tag. These transformations are where most confusion arises if lineage is not maintained.

3. Destination

This is where the data is ultimately used — often by FMs. The CMMS, dashboards, digital twins and analytics platforms all rely on incoming data, assuming it is correct and complete. Importantly, a single source data item may appear in multiple destinations. It might show up in a monthly performance report, feed into a real-time fault detection dashboard, and be used as input in a cost analysis or energy model. If the source data is inaccurate or becomes disconnected, it can create a cascade of downstream issues that are difficult to trace without a lineage map.

FMs typically work at the “destination” end of this chain. But when problems arise, the issue often starts upstream: in the source or transformation stages.

Lineage from design to operation: A life cycle story

To illustrate, here is an example tracing the life cycle of a generic rooftop unit (RTU) from design through operations:

• Design stage: The unit is first specified in a BIM model, with attributes like airflow, voltage and zone assignment.

• Construction & commissioning: That model is used to generate COBie worksheets and IFC files, which are shared with contractors and systems integrators. The RTU is installed and connected to the building automation system.

• Handover: The asset is registered in the CMMS. A technician enters a new identifier, unaware it already exists in the design model under a different name.

• Operation: A sensor tied to the unit begins reporting airflow data. it is linked in the BMS but not cross-referenced in the CMMS or digital twin platform. Over time, a dashboard flags inconsistent readings — but without lineage, the facilities team cannot tell if the issue is with the sensor, the asset ID or the analytics rule.

This kind of disconnect is not uncommon. It occurs when data travels through the building life cycle without a consistent identity or traceable path. Data lineage helps rebuild that path, so each value in the system can be trusted, verified and understood in context.

Behind the scenes: How lineage gets built

The good news is that facility managers do not need to build lineage maps themselves. That work is typically done behind the scenes by data lineage platforms, often administered by IT or data governance teams.

These platforms capture metadata about how data moves between systems. Think of it as creating a digital paper trail: every time a piece of data is created, transformed or consumed, the system notes who did it, where it went and what changed.

Visualizations are often used to display this trail. Like a subway map, lineage diagrams show the data’s route from origin to destination, with color-coded paths for each transformation.

Other tools compare versions of data models over time, flagging changes and helping organizations answer the question: What changed — and why?

Facility professionals do not need to operate these tools, but having a general awareness of how they work is important. When data issues arise, knowing that lineage maps exist — and how to reference them — can lead to faster diagnosis and better communication with IT and system administrators.

Where are the benefits of implementing data lineage?

While data lineage platforms are rarely deployed directly by facilities departments, their impact is increasingly felt across operations:

• Data confidence: When every data point has a verified source, teams can make decisions faster and with less second-guessing.

• Faster resolution: When issues arise, lineage allows staff to trace back through systems and pinpoint where the problem started, saving hours of manual investigation.

• Improved reporting: Accurate reporting requires trustworthy data. Lineage provides the audit trail that connects each metric to its origin, ensuring compliance and reliability.

• Digital twin enablement: Digital twins and smart building platforms rely on clean, synchronized data. Without lineage, a digital twin may show real-time values that no one can validate.

Most data lineage systems are built and managed by technology specialists, often under the umbrella of data governance or enterprise IT programs. However, FMs should develop awareness of lineage concepts so they can communicate effectively with technical teams when data inconsistencies occur or trust is in question.

As buildings grow more connected, the line between facilities and IT teams is fading. Lineage becomes the shared language that both sides can use to understand what went wrong — and how to make it right.

Conclusion

As the built environment becomes more digitized, facility professionals find themselves surrounded by data. Some of it is critical, some of it is operationally essential and much of it is interconnected. But without context, that data is just noise.

Data lineage provides the context

It allows a facility manager to see not only what the data says, but where it came from, how it got there and who touched it along the way. That visibility turns data from a liability into an asset — from a source of confusion into a tool for confident action.

In a world of smart buildings and real-time analytics, being able to ask, “Where did that data come from?” — and get a clear answer — is no longer a luxury. It is a necessity.

Facility managers do not need to become data scientists; but they do need to speak the language of data with clarity, especially as their roles increasingly intersect with IT, automation and analytics. Understanding data lineage is a powerful step in that direction.

There are several platforms and programs available. To start, web search “vendor-neutral data lineage platforms” to find providers, resources and example tools that illustrate how data lineage is mapped, visualized and maintained in enterprise environments.