Technology aims to add value.

The internet revolutionized information access, and the processor has revolutionized data processing. We now have more computing power in our pocket than generations before had in their office.

As shared by Deloitte, this has led to some of the major technological advances today: the “internet of things,” big data, machine learning, artificial intelligence, and data analytics.

Kern County, a leader in energy production, is leveraging these technologies to improve decision-making. According to The Bakersfield Californian, our county is currently the wind turbine capital of the world and has the largest solar energy project in California. The Kern County Economic Development Corporation shows our county is one of the top-oil producing counties in the United States.

The intermittent energy sources (solar and wind) also lead to challenges with the existing grid infrastructure according to OEP, a nonpartisan, nonprofit organization focusing on energy discussions.

With such a high level of energy production and challenges in distribution, there are plenty of opportunities to improve and optimize processes to add significant value. Some examples include IBM Smarter planet, which predicts weather patterns to improve wind and solar installation locations. Work done by T. H. Kim, D. J. Crane and E. F. Grijalva has shown methods of predicting remaining oil reserves to optimize drilling programs and work by LNS Research predicts safety risks based on job type and location. The Deloitte center for energy solutions highlights how some of the challenges with the grid can be addressed by distributed energy resources, or DERs.

There is an abundance of data. Sensor costs have significantly decreased, computational power has significantly increased and most companies have terabytes upon terabytes of data. There is also a potential advantage of using an algorithm or predictive software to make decisions.

“Decisions made with better data analytics tend to routinely lower risk by reducing the impact of the human experience and emotional tendencies,” wrote Iraj Ershaghi, Milad A. Ershaghi and Andrei Popa in an article on data ethics in oil and gas operations.

However, there is the challenge of data quality when making good business decisions.

There’s an adage: “Garbage in, garbage out.” If the data being used to make decisions is compromised, the results will be as well. That is where the human element is key. It is important to have people who understand the data, know the variables that have the most impact and can quality control the data to improve the predictability of the algorithm.

There is no doubt that technology has the potential to be of great value. Transitioning it from potential to reality will require data accuracy. Sometimes, it’s about the quality of the data in making better decisions, not just the quantity.

Tarang Lal works in the energy industry and has a blog focused on energy education, Tuesday’s with Tarang. You can follow him on LinkedIn.

(1) comment


Tarang, very insightful article when dealing with data quality vs. quantity. With the explosion of big data companies are faced with data challenges in three different areas. First, you know the type of results you want from your data but it’s computationally difficult to obtain. Second, you know the questions to ask but struggle with the answers and need to do data mining to help find those answers. And third is in the area of data exploration where you need to reveal the unknowns and look through the data for patterns and hidden relationships. The open source HPCC Systems big data processing platform can help companies with these challenges by deriving insights from massive data sets quickly and simply. Designed by data scientists, it is a complete integrated solution from data ingestion and data processing to data delivery. Their built-in Machine Learning Library and Matrix processing algorithms can assist with business intelligence and predictive analytics. More at

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