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Many utilities' problems with data management begin with the tools they employ to gather data.
Fremont, CA: The electricity industry is about to undergo its most significant change in decades. The industry has to reach net zero by 2035 to satisfy the goals established by the Biden administration. While worries about new pollution restrictions are growing, forward-thinking utilities understand that investor trust is the greater prize.
According to a survey, a company's energy transition plan is crucial to determining its creditworthiness. Investors perceive carbon-intensive activities as a business risk and, consequently, as a danger to their returns.
Many investor-owned utilities have responded by implementing their ESG efforts and net-zero goals. The onus is now on them to demonstrate that they are keeping their commitments. These factors are causing a rise in data complexity and volume, making it more challenging for utilities to retain, manage, and use emissions data. The requirement for increased access to reliable, timely data is growing along with the need to report on these activities.
Data collection
Many utilities' problems with data management begin with the tools they employ to gather data.
By gathering emissions data directly from the source and combining it with data from other systems, companies can add value to the existing data and gain insights that will help them make better strategic decisions.
Data visibility
A significant blind spot in the electricity industry is data visibility. Data visibility issues can negatively affect compliance performance and impede responses to nonconformity, incurring hefty fines and penalties. Additionally, a lack of data visibility might make it difficult for utilities to comply with new mandatory and voluntary standards.
In reality, the utility sector has crossed a critical threshold at which a lack of data visibility is intolerable. Moreover, such issues will only worsen when utilities launch new programs like smart grid technologies and electric car charging stations.
Data volume
The sheer amount of data also poses a considerable problem. Think about the various sources that one plant's emissions data might come from. Thousands of distinct data points are produced by continuously monitoring these sources; these points must finally be cleaned, sorted, formatted, and organized for usage.
Maintaining clean, full, and up-to-date emissions data becomes considerably more challenging when you multiply it by all company processes. It can take up to an 80percent of the time to process all of this data, leaving little time to use the data.
By automating these procedures, a modern cloud-based solution enables environment engineers to analyze massive amounts of data at the source and frees up their time for analysis.
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