---
title: "DCCEEW Microsoft Fabric Case Study | Data-Driven AI"
canonical: "https://data-driven.com/case-study/how-dcceew-modernized-their-biodiversity-offset-scheme-with-microsoft-fabric/"
description: "See how DCCEEW used Microsoft Fabric to consolidate Biodiversity Offset Scheme data, automate nightly processing, and feed Power BI reports."
---

NSW DCCEEW · Biodiversity Offset Scheme

# DCCEEW brought scheme data onto _Microsoft Fabric_

A medallion data model replaced manual SSIS work and gave Power BI reports a curated Fabric source.

![Hexagonal icons for renewable energy and environmental measures beside a trend chart](/_astro/14-2.Dymf3qHW_Zvdi62.webp)

Project snapshot

## Bring scheme data into a controlled reporting path

The NSW Department of Climate Change, Energy, the Environment and Water manages data for the Biodiversity Offset Scheme. Its published project record describes source files, legacy SSIS jobs, an on-premises warehouse, and separate Power BI workspaces.

### About the scheme data

The department publishes registers for biodiversity credit supply, demand, and transactions. The Fabric project concerned the department’s wider internal scheme data and reports.

[View the official public registers](https://www.environment.nsw.gov.au/topics/animals-and-plants/biodiversity-offsets-scheme/maps-systems-and-resources/public-registers).

> “Data-Driven’s implementation based on Microsoft Fabric has now automated our data integration from various sources and set a foundation for a consolidated data estate long-term. We can now analyse our data more efficiently and make informed decisions faster. Further, our new Microsoft Fabric Data Platform has given us an excellent source for our key Power BI Reports and removed our dependencies on direct-to-source reporting. Data-Driven helped enable our transition to Microsoft Fabric and to discover, ingest and consolidate source data.”

Durvesh Chattopadhyay

Data Management, BOS Digital Transformation Team

Starting point

## Source data and report work were spread across platforms

The published record ties the delay to both data movement and data quality work.

1.  SharePoint CSV and Excel files sat beside BOAMS and warehouse data.
2.  Legacy SSIS jobs and manual corrections added processing work.
3.  Separate Power BI workspaces depended on direct source connections.
4.  Consolidated reporting could take up to ten days, as recorded for this project.

Fabric data path

## Each medallion layer had a clear data job

Nightly Fabric pipelines moved source data into OneLake. Fabric pipelines and notebooks then cleaned and joined it. Curated tables supplied the Power BI reports.

1.  Bronze kept raw SharePoint, BOAMS, and warehouse data in OneLake.
2.  Silver standardised names, dates, times, and lookup values.
3.  Gold held curated tables for scheme reports and analysis.
4.  Role-based access limited who could view or change records.

Published result

## Data preparation fell below two hours

The timings below are recorded for this Biodiversity Offset Scheme engagement. They are not a benchmark for other Fabric projects.

10 days

Reported maximum delay for a consolidated report

<2 hrs

Reported end-to-end data preparation time

Nightly

Recorded pipeline schedule

Control boundary

## The case records access design, not compliance

The project record names role-based access and curated data layers. It does not publish a compliance finding, security test, or certification.

### Keep the result tied to this data estate

The source mix, processing rules, report cycle, capacity, and review process must be measured again for another workload.

## Discuss a Fabric data-platform brief

Bring the source systems, report delay, quality checks, access roles, and data owner. We will use them to define the first workload.

[Contact Data-Driven](/contact-us/)

[Back to home](/)

## Want to learn more?

Explore the rest of the site or get in touch with the team.

[Back to home](/)