Overcoming the challenges of incomplete big data

Data has emerged as a critical asset for electric utilities driving progress, efficiency, innovation, and customer satisfaction. The introduction of smart grid technology and advanced metering infrastructure has provided utilities with a wealth of information about energy consumption, grid performance, and customer behavior. However, amid the rapid digitization of the energy sector, it’s essential to recognize the limitations of data and consider ways of addressing them.

Incomplete and Inaccurate Data: One of the primary challenges faced by utilities is the incompleteness and inaccuracy of data. These gaps and errors can hinder accurate analysis and decision-making, as incomplete data sets fail to provide a comprehensive understanding of energy usage patterns and grid performance.

Investing in advanced metering infrastructure and data collection tools such as hand-held devices can help. These tools can not only feed automatically into analytics applications, but they can also help identify and rectify any errors or gaps.

Data Silos and Lack of Standardization: Another limitation lies in the presence of data silos within utility systems. Different departments within utilities often manage their data independently, resulting in fragmented information repositories.

Grid management through the implementation of a system-wide analytics software facilitates cross-departmental collaboration and data sharing. Over time, organizations can perform standardized analysis and investment planning across different departments.

Data Overload and Analysis Paralysis: The sheer volume of data generated by smart grids can be overwhelming. Extracting actionable insights from such large datasets requires advanced analytical tools and expertise, posing a challenge for utilities with limited resources and capabilities.

Promoting a data-driven mindset and encouraging data literacy within the organization through the use of databases and asset management tools encourages the entire organization to take part in streamlining and organizing data. Providing access to all utility employees also encourages democratization of information.

Data has the potential to revolutionize the way utilities operate if they actively prioritize data quality and interoperability, as well as cultivate a data-driven culture. Utilities can overcome the limitations brought on by incomplete big data and harness its full potential to drive efficiency, sustainability, and innovation in the energy sector.


Aleksandra Modelewska has 10+ years’ experience in the power systems industry, helping electrical utility representatives navigate new technologies and innovation. She is an advisory committee member of Women in Renewable Energy (WiRE) and the Chair of CIGRE Canada’s Next Generation Network. Over the years, Aleks has managed international interest groups focusing on utility asset management, grounding & lightning, as well as protection & control and overhead line design. She has also been involved with venture growth and marketing while leading business development efforts in Canada, the USA, Europe and Australia.

As Director of Business Development & Sales at Engineered Intelligence, Aleks will help energy companies automate their asset risk analysis and power system planning.

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