Introduction to Sustainability data solutions in Microsoft Fabric
For organizations to solve the environmental, social, and governance (ESG) challenges, they need to collect and transform disparate data into standard-driven and analysis-ready data to support the sustainability use cases.
Sustainability data solutions in Microsoft Fabric offer unique capabilities to ingest, harmonize, and process disparate ESG data for specific sustainability scenarios. By using this solution, organizations can build a comprehensive data estate, centralizing and transforming data from across business units and supply chains into a standard schema. Organizations can use this data estate for advanced analytics and reporting. For more information, see Overview of Sustainability data solutions in Microsoft Fabric.
Sustainability data solutions in Microsoft Fabric architecture
Microsoft Fabric is an all-in-one analytics solution for enterprises. It covers data movement to data science, Real-Time Analytics, and business intelligence. It offers a comprehensive suite of services, including data lake, data engineering, and data integration, all in one place. For more information, see Get started with Microsoft Fabric.
Sustainability data solutions in Microsoft Fabric empower organizations to bring together ESG data from data sources, such as business systems, unstructured data, semi-structured data, sensor data, and non-Microsoft datasets. Then, organizations can standardize the data by using the ESG data model to build a centralized ESG data estate. It consists of unique capabilities that provide prebuilt and preconfigured Fabric resources. These resources include data stores in the form of data lakes, prebuilt notebooks, and dashboards to ingest, process, aggregate, and display data for various ESG scenarios. The Microsoft Fabric resources that are associated with each capability are deployed to a Fabric workspace in your tenant, and you can set up the resources for your sustainability needs.
Important terminology in the Fabric architecture includes:
Interoperability for sustainability - Uses Microsoft Fabric resources for data ingestion, transformation, governance, and sharing. These components integrate unstructured data from various sources into Microsoft OneLake.
Microsoft Fabric - Helps you manage your data in one place with a suite of analytics experiences that work together, including Microsoft Azure Data Factory, Synapse Data Engineering, Synapse Data Warehousing, Synapse Data Science, Synapse Real Time Analytics, and Business Intelligence using Microsoft Power BI, and Data Activator.
OneLake - Stores and transforms data into a standard format by using a sustainability analytical schema.
Sustainability data solutions in Microsoft Fabric - Helps you ingest, transform, and manage your data in OneLake. The capabilities of this solution include ESG data estate, Microsoft Azure emissions insights, environmental metrics, and analytics, in addition to social and governance metrics and reports.
Sustainability data solutions capabilities
Sustainability data solutions in Microsoft Fabric have the following capabilities:
ESG data estate - This capability allows you to combine ESG data from various sources into a standard schema that provides data models for environmental, social, and governance records. For more information, see ESG data estate.
Microsoft Azure emissions insights - This capability helps you centralize, query, and analyze your Azure emissions data. For more information, see Microsoft Azure emissions insights.
Environmental metrics and analytics - This capability helps you directly connect your environmental data from Microsoft Sustainability Manager to the data lake as tables without the need to reingest it. For more information, see Environmental metrics and analytics.
Social and governance metrics and reports - This capability allows you to combine disparate data from various sources into a standard schema that provides data models for social and governance records. For more information, see Social and governance metrics and reports.
