Data quality in the utility industry is essential for both creating new energy sources and reducing our carbon footprints.
We look to renewable energy sources like solar and wind power as modern technological advancements. In increasing numbers both businesses and individuals are installing solar power systems to cut costs and protect our environment. Wind farms dot almost every rural area in the U.S. adding clean power to the inventory of various utility grids.
However, building renewable energy sources isn’t the only way to save electricity and protect the environment. Utility companies can also analyze data to comb through customers’ electricity habits, uncovering energy savings and carbon footprint reduction potential. By using energy sensors, utilities monitor energy outputs and provide customers with strategies to optimize their reduction in electricity consumption.
There are also substantial regulations in the utility industry. Proving compliance is impossible without a complete and accurate understanding of the properties, quality and availability of data assets. Consequently, utility companies need high-quality information to leverage data, uncover energy-saving opportunities, while also mitigating compliance risks.
Like other industries, utility companies deal with a wealth of customer, vendor, third-party and even machine data. Still, many utility organizations lack the knowledge and IT infrastructure to manage and benefit from their information assets. Their data is often siloed and underutilized, making it nearly impossible to collectively use for any type of analysis. Without the ability to trace and remediate bad data, data processes requiring automation and efficiency fail and regulatory reporting suffers.
Business users can’t take advantage of siloed information. When data is stored within various locations and systems, business users can’t find pertinent customer or operational information to identify and explore new ways to make cost-saving decisions. Each department tends to maintain within their own pocket of knowledge, data sets and “sources of truth”.
Siloed information isn’t just a barrier to cost containment, but it negatively impacts customer service, business decisions and company culture. With manual data processes, users must piece together analysis reports from inconsistent sources, lacking clarity into compliance, losing trust in data and dramatically impacting the utilities bottom-line.
Data quality in utility industry is fundamental to any data governance framework. However, many organizations lack a cohesive strategy for governance and data quality. A data governance program with an integrated quality solution provides utility companies with a foundation for protecting end-to-end data quality. Comprehensive quality rules between sources and systems assure companies maintain data integrity and hold data suppliers accountable for quality data.
Modern technologies can also automate processes to decipher data lineage and empower data users at utility companies to quickly understand, access and apply enterprise data for business purposes. For example, a data intelligence platform with automated 3D data lineage technologies. 3D lineage automatically links technical and business layers, connecting data to business processes and business knowledge.
Having a data intelligent platform that also builds a detailed data catalog by automatically profiling data, extracting metadata and documenting information in the catalog is crucial to healing and uncovering broken data. The data catalog then provides a single, searchable source of data knowledge for various business areas. The catalog educates data consumers regarding data quality levels, meaning, ownership and usage, building trust and encouraging data utilization.
Ensuring data quality builds trust among users who utilize information to identify where customers can reduce energy usage and develop and promote programs, incentives, discounts and online tools. Data quality also provides an enriched understanding of enterprise data to ensure compliance with a wide variety of complex regulations.
Are you looking for additional information about enhancing data quality and data value in the utility industry? Check out this case study: https://www.infogix.com/resources/midwestern-utility-executes-an-innovative-enterprise-data-strategy/
For additional information about managing data quality, read this article: https://tdwi.org/articles/2019/04/19/diq-all-data-quality-in-the-age-of-big-data.aspx
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