What You Need to Know: A data lakehouse isn't an IT concept that happens to touch preconstruction. It's the answer to a problem preconstruction teams have always had: historical estimating data that exists but can't be used. A data lakehouse is a managed, structured repository of every estimate your team has produced - organized, current, and ready to query - that replaces the export-and-reconcile pattern with a single source your team can build reporting and intelligence against directly.
When preconstruction teams hear "data lakehouse," the instinct is often to forward the email to IT. It sounds like infrastructure. It sounds like something that lives in a data center and matters to analysts who write SQL queries.
But this concept is important to estimators - just not for the reasons the terminology suggests.
The problem data lakehouses solve is a preconstruction problem - one that every team with more than a year of project history has experienced. The data exists. Years of estimates, line items, assemblies, cost categories, scope breakdowns, fees, and the decisions behind all of them. But when someone asks a question that requires looking across that history - how does this school compare to our last three schools? where are our concrete estimates consistently off? - the answer requires finding old files, exporting data from individual projects, cleaning it up, and manually assembling something resembling an answer.
The data exists. It just doesn't exist in a form that answers questions.
A data lakehouse changes that. It takes the preconstruction data that's been flowing through DESTINI Cloud and puts it into a single, structured, continuously-updated environment where questions can be asked directly, without exports, without manual reconciliation, without someone spending a day assembling data that should already be assembled.
In enterprise data environments, a data lakehouse combines the scalability of a preconstruction data lake with the structured queryability of a database. That's the technical definition. It's accurate and not particularly useful for someone who needs to understand what it means for how their preconstruction team works.
A more useful definition is that a data lakehouse is a place where all your estimating data lives together, organized consistently, and always current - so that instead of asking "where is that data?" you can ask "what does that data tell us?"
DESTINI Analytics gives every customer organization a dedicated data lakehouse that Beck Technology sets up, maintains, and keeps current, containing the full content of every estimate your team has produced in DESTINI Cloud.
Your organization's preconstruction data is isolated from other customers both physically and at the access layer. What's in your data lakehouse reflects your estimates, your line items, your cost structures, your project history. It's yours, it's current, and it's query-ready the moment you need it.
The most important thing to understand about how a data lakehouse works is also the thing that makes it different from every export-based workflow it replaces: the data flows in continuously, automatically, without any action required from your team.
Every change made in DESTINI Cloud - a line item updated, a scope revised, a fee adjusted, an estimate published - flows into the data lakehouse immediately through a cloud storage layer that captures changes automatically. There are no save events to trigger, no batches to wait for, and no exports to schedule. No one needs to remember to push data to the reporting system before a Monday morning review.
The data lakehouse always reflects the current state of work in DESTINI Cloud. Reports built on the data lakehouse don't show yesterday's data or last week's snapshot - they show what's in the platform right now, updated within minutes of any change.
This is crucial when estimates are actively evolving. During design development, when costs change with every drawing revision, a reporting environment that depends on manual exports quickly falls out of sync. Teams end up reviewing analysis that doesn't reflect the current estimate. Decisions get made based on yesterday's numbers. The data lakehouse eliminates this by treating continuous data flow as the baseline instead of an advanced feature.
The DESTINI Analytics data lakehouse is organized into three layers. Each serves a distinct purpose, and the separation is what keeps reporting stable even as the underlying data changes.
The raw layer is an untouched archive of every estimate exactly as it was produced in DESTINI Cloud. It never gets modified. This layer exists for two reasons: it's your permanent record, and it's the foundation that allows everything downstream to be rebuilt if the data structure ever needs to evolve. If Beck Technology adds new fields or changes how data is shaped, the raw layer lets that work happen without disrupting the reporting your team depends on. Think of it as the source of truth that never changes, so everything built on it can.
The refined layer is where the raw data gets cleaned, typed correctly, and reorganized into a stable set of tables: estimates, line items, fees, scopes of work, cost categories, and the metadata that connects them. This is the layer most analysts would query directly. It's predictable and designed for questions like "give me all the mechanical line items from healthcare projects in the last three years." The schema stays stable - Beck Technology treats it as a contract, meaning column names and table structures don't change without advance notice and a migration path.
The reporting layer is a polished, user-friendly version of the refined preconstruction data with descriptive column names, pre-built calculations, and relationships that make sense to people who aren't data engineers. This is what powers the embedded reports inside DESTINI Cloud - the dashboards that appear directly in the platform without requiring any technical setup from the people viewing them. It reads continuously from the refined layer, so reports are always current without any separate refresh.
The three-layer structure solves a problem that anyone who has built reporting against a live system has experienced: if the data structure changes, your reports break. By separating the raw archive, the clean analytical layer, and the reporting layer, DESTINI Analytics ensures that changes in how estimates are structured don't cascade into broken dashboards - and that the data your team queries tomorrow will work the same way it did today.
The data lakehouse contains the full content of your estimates, structured so they can be queried alongside every other estimate your team has produced. That includes:
This is the data that answers the questions preconstruction leaders actually ask: How does this estimate compare to similar projects? Which cost categories are running higher than historical? What's our average cost per square foot for this building type in this market? Where do our estimates consistently diverge from actual costs?
None of those questions can be answered by looking at a single estimate. They require looking across estimates - which is exactly what the lakehouse enables. The data model can also be extended on request if there are specific fields in your workflow that need to be surfaced.
Once the data is in the lakehouse, there are four distinct ways to put it to work. Most customers use more than one, depending on who's asking the question and what they need to do with the answer.
Reports built into DESTINI Cloud are the starting point for most teams. Pre-built dashboards covering the most common questions - estimate trends over time, cost category breakdowns, fee analysis, historical comparisons - appear directly in the platform under an analytics section. The preconstruction analytics live where the estimating work already happens, visible to anyone with a DESTINI Cloud login whose role permits it.
API access is the path for teams that want to pull DESTINI Cloud data into other systems - a project management platform, an ERP, a custom internal application, or an enterprise data warehouse. The same preconstruction data that feeds the lakehouse is available through standard REST endpoints, authenticated and scoped to your organization, with the same low-latency updates. The API is the right choice for operational integrations and event-driven workflows. It requires no Microsoft Fabric setup on the customer side.
Direct table access gives data teams read-only access to the underlying lakehouse tables from their own Microsoft Fabric environment, through a feature called OneLake table sharing. The preconstruction data stays in Beck Technology's infrastructure, but your analysts can query it as if it were native to their tenant. This is the path for teams that want to blend DESTINI Cloud data with their other data sources: accounting, project management, CRM, market data. It requires a Microsoft Fabric capacity on the customer side.
Embedded custom reports allow teams that have built their own Power BI reports - against the data lakehouse, or against other data sources entirely - to surface those reports inside DESTINI Cloud. The reports stay in the customer's Power BI workspace. Beck Technology authenticates against that workspace at render time. The result: every estimator on the team sees custom analytics directly in the platform, while the data team retains full ownership of the reports and the underlying logic.
These four paths are designed to work together rather than requiring a choice between them. A typical progression starts with the built-in reports for immediate value, adds API access when system integrations become relevant, brings the data team in via direct table access when custom analysis is needed, and eventually embeds custom reports back into DESTINI Cloud so the broader estimating team benefits from the data team's work - without leaving the platform.
The difference that a lakehouse enables is primarily organizational.
Most preconstruction teams have been archiving historical data for years without being able to use it. Estimates get filed. Projects close. The data sits. When someone wants to know what similar work has cost historically, the answer requires finding files, exporting data, and manually assembling a comparison that should already exist.
The data lakehouse makes that comparison always available because the structure of the data makes it query-ready by default. Every estimate that flows through DESTINI Cloud becomes part of an organizational dataset that grows more valuable with every project added.
This is the evolution from archive to a system of intelligence. Data that previously existed as a historical record becomes a living resource that informs current decisions. Historical cost comparisons that required hours of data assembly happen in seconds. Patterns that no individual estimator could identify across hundreds of projects become visible because the data is structured to reveal them.
Intelligence requires solid data. The lakehouse is where that data lives - organized, governed, continuously current, and ready to answer the questions preconstruction teams have always had but haven't always been able to ask.
See what your historical data can do:
Learn More About DESTINI Estimator →