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Overview of data import

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Companies communicate their sustainability performance and impact on a wide range of topics, spanning environmental, social and governance parameters. Data collection is one of the most important steps in the process of defining your company's greenhouse gas emissions and carbon footprint. Sustainability Manager's data ingestion engine provides a guided process for you, no matter your experience level, to successfully import your data and obtain quicker insights into your carbon and sustainability performance.

You can bring in deconstructed data sets from one or multiple sources and use the capabilities of our ingestion engine, reducing the time and resources required to transform the data. The import flow provides a simplified experience and flexibility to enable adoption.

Sustainability Manager provides guided experience that helps you complete these tasks:

  • Identify data requirements and use preferred methods for data collection.

  • Take advantage of the capability to develop data collection procedures, tools, and guidance materials.

  • Compile and review facility data, such as data about electricity and natural gas.

  • Estimate missing data to fill in gaps.

  • Select predefined emission factors.

  • Calculate emissions and sustainability performance across different levels in your company.

Import methods

You can add data in Sustainability Manager in multiple ways, depending on the data type, source, user experience level, and import frequency. These different methods help you to connect as closely and directly as possible to your data sources.

You can import data with the following methods:

01.

You can use any of these methods to import data based on your knowledge and understanding. Each approach includes detailed guidance for every step of the import process, plus example data to ensure that your data import is successful.

For more information and answers to frequently asked questions, check out the following links:

Reporting period definition

Sustainability Manager includes the capability to create and manage reporting years for customers. The creation of a reporting year enables organizations to name their reporting year, define the starting date and apply a template to determine the number of periods to create. Once created, the reporting year is available for selection on the insight pages.

Important

A known limitation of closed periods occurs when ingesting data into an open period. If its origin correlation ID (OCID) belongs to a record in a closed period, then that record is updated to adhere to the new date and values.

Reporting periods have a default status of open. To provide enhanced audit control, a period can be closed to prevent changes to data. Select the Status dropdown and select either Open or Closed. A period in an open state allows new records to be created and existing records to be edited. When a period is closed, the system prevents any calculations, data import, data creation, modification, or deletion of records in that closed period.

Data approval management (preview)

Data approval management (preview) allows you to stage data in a pending state such that it isn't impacting calculations, analysis and reporting. After review and approval by authorized users, the data becomes available for all corresponding functions. You can enable data approval management for all or only selected data types entities as needed. Records in data type categories that aren't enabled for data approval management are autoapproved. Likewise, all records created in versions before data approval management introduction are autoapproved.

The feature is disabled by default. However, when enabled, all data approval management-enabled records are created in a pending state. Pending records are still visible in record registers.

Data import terminology

Data import: Importing data from various accounts by using a set of prebuilt actions and triggers.

Import mapping: Action to map the fields in the source data with the fields for specific entities within our data model.

Source field: Field names defined in the data source that are being imported into Sustainability Manager.

Destination field: Attribute or field names defined for a specific entity within our data model.

Auto map: Automatically mapping the source fields with the destination fields.

Data transformation: Process of converting data from one format to another. Sustainability Manager converts source data into the required format that aligns with our data model.

For more terms and definitions, go to Glossary.

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