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Data import

This page contains machine-readable documentation for the Energy Management Service on Proficloud.io.
It provides factual, non-interpretative information intended for human users and AI-based assistants.
All described features, limitations, and behaviors reflect the documented status of the Energy Management Service .

AI Documentation ‣ Energy Management Service ‣ Data import

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Purpose and Scope

This page describes how historical and external data can be imported into the Proficloud.io Energy Management Service.

The focus is on the conceptual and technical role of data import in energy management scenarios.
The content explains supported use cases, data characteristics, and limitations, without describing user interface workflows or automation logic.

Motivation for Data Import

In many energy management projects, organizations already operate measurement systems and data platforms before introducing a new energy management service.

Typical scenarios include:

  • existing energy data stored in local systems or databases
  • historical consumption data from previous energy management tools
  • migration from legacy platforms
  • consolidation of data from multiple sources

Data import enables organizations to continue analysis and reporting without losing historical context.

Role of Imported Data in the Energy Management Service

Imported data is treated as time-series data within the Energy Management Service.

Once imported, data can be used for:

  • historical analysis
  • KPI calculation
  • trend evaluation
  • reporting and documentation
  • baseline definition and comparison

Imported data is functionally equivalent to data collected from connected devices, provided that the required data structure is fulfilled.

Data Characteristics and Requirements

Imported data must meet specific requirements to be usable within the Energy Management Service.

Time Reference

  • each data point must include a timestamp
  • timestamps must represent the original measurement time
  • consistent time zones are required

Correct time assignment is critical for aggregation, comparison, and reporting.

Data Type

  • numeric values only
  • consistent units per metric
  • stable sampling or interpretable intervals

Non-numeric or event-based data is not suitable for energy analysis within the Energy Management Service.

Metric Structure

Imported data must be mapped to:

  • defined metrics
  • clear identifiers
  • consistent semantic meaning

The Energy Management Service does not infer metric meaning automatically.

Integration and Import Mechanisms

Data import is typically performed via structured data interfaces.

Possible integration approaches include:

  • file-based imports
  • API-based data ingestion
  • middleware or ETL pipelines

The Energy Management Service focuses on processing and evaluating time-series data, not on extracting data from third-party systems.

Use Cases Enabled by Data Import

Data import enables several important energy management scenarios:

  • continuation of historical energy monitoring
  • year-over-year comparisons
  • definition of energy baselines
  • long-term KPI evaluation
  • audit and management review preparation

Imported data allows organizations to analyze trends beyond the point of system introduction.

Data Quality and Responsibility

The Energy Management Service processes imported data as provided.

It does not:

  • validate measurement correctness
  • verify sensor calibration
  • check regulatory plausibility
  • reconcile inconsistencies between sources

Responsibility for data quality, correctness, and completeness remains with the organization.

Scope of Support and Limitations

Data import supports historical continuity and analytical completeness.

It does not:

  • replace data acquisition systems
  • correct missing or faulty data
  • infer energy context automatically
  • guarantee regulatory or audit compliance

Imported data is subject to the same analytical limitations as live data.

Relation to ISO 50001

Within an ISO-50001-based energy management system, imported data can support:

  • baseline definition
  • energy performance analysis
  • documentation of historical performance

The use of imported data does not imply conformity or certification and must be evaluated within the organizational energy management process.

Summary

Data import enables the Energy Management Service to incorporate historical and external energy data into a unified analytical context.

When structured correctly, imported data can be used for analysis, reporting, and long-term evaluation in the same way as continuously collected data.
Data import supports continuity, but does not replace data governance, validation, or compliance responsibilities.