Sigma Online User Manual
Monitoring Periodic Data
Good quality data is crucial for your business. It is the key to compliance, streamlined budgeting, and surpassing carbon reduction targets. It also provides ultimate portfolio transparency in the mission to drive down consumption.
To facilitate the most accurate monitoring, targeting and reporting of energy and consumption, data needs to have the following attributes to achieve quality:
- Accuracy – data correctly reflects what is being measured and its expected behaviour
- Completeness – all expected data is present and without gaps
- Consistency – data conforms to a required format that agree with each other
- Timeliness – data is available to support fulfillment of energy management duties on time
Data that is not accurate, complete, consistent, and timely can lead to:Â
- False reporting
- Ill-conceived energy strategies and activities
- Unreliable forecasting, capacity management, and procurement strategy
- Flawed compliance submissions (SECR, GHG, for example)
- Disengaged stakeholders who no longer trust the reports and data they are seeing
Sigma’s data monitoring suite promotes proactive energy management with robust and auditable data, supporting these four pillars of data quality. Reliability and completeness of information is assessed for you - a scheduled task will monitor data related issues in high frequency data (HFD) periodic channels as per your configuration, identifying and recording notifications and automatically closing them where they have been resolved.
There are two pre recorded training sessions on data monitoring, please use the links below.
**Click here for a pre recorded training session for additional help and guidance - Identifying Data Gaps using the Data Monitoring ActivityÂ
**Click here for a pre recorded training session for additional help and guidance - Monitoring Trends in HH Data which includes details on Fixed and Dynamic Profile Strategies
The following Online Help Pages are available:
- Introducing Data Monitoring
- Explanation of the Data Monitoring Activity
- Creating Data Monitoring Strategies
- Managing Strategy Notifications
- Resolution Logic for Data Gaps or Overdue Data
- Maintaining Data Monitoring Schedules
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