Today there is more data than ever. In fact, the total amount of the amount of data has, recorded, recorded, copied and consumed worldwide, has now reached an incredible 149 Zettabyte. The growth of the large mountain is also not expected that it will probably reach almost 400 Zettabytes in the next three years.
While more data generally leads to more insights, the quality of these findings can only be as good as the quality and relevance of the data, which ensure that the correct data are of crucial importance not only in terms of volume, but also in context and accuracy. Nevertheless, it can be a real challenge to keep data clean and true. This applies in particular in regions in which the number of deregulated supply companies means that electronic data exchange (EDI) can be slow and inconsistent. As soon as this poor data infiltrate the system, problems begin.
To become smart to alleviate the problem
Intelligent measuring devices are a more sustainable future for everyone. They enable the industry to better manage the energy required and where. This means reducing energy waste and making less dependent on traditional fossil fuels.
Intelligent meters are also significantly contributed to alleviating the problem of poor data. Despite the well -published advantages of intelligent meters to help consumers to better pursue their energy consumption and to maintain more precise bills, their introduction is still behind the first forecasts in many regions. Here it is still common for employees of supply companies to visit rooms to physically read counters.
In these regions, it is absolutely necessary that energy companies do what they can do to clarify consumers about the long -term advantages of intelligent meters and implement pilot programs in order to demonstrate their effectiveness. Regulatory support and incentives can also have contributed to accelerating the acceptance rates and promoting more to the transition to the smart meter technology.
Do you know your customers
However, it is not just about knowing which energy is consumed at any time, but by whom. Know your customer guidelines (KYC), which a supplier have to verify identity, suitability and risks for maintaining a business relationship with a customer to support debt and fraud prevention. It is good on paper, but not infallible. The human error or confusion at the input point can be common. For example, the same customer could be entered as Dave, Dave, David, David, Davd or more.
Every company has to decide how aggressively scrubbing its data in order to remove wrong -positive results. The time came to the time. Fortunately, innovative tools are now available that can help so that bad data no longer affect the downstream effects on others. Using such a tool and ensuring that the correct steps and measures are available so that every “David” would primarily enter correctly, can help keep the data error free.
Convert data into implementable knowledge
Artificial intelligence (AI) and machine learning (ML) are at the top of the conversion of data into implementable knowledge for the energy industry. These technologies are characterized in the analysis of complex data records, the identification of patterns and the prediction of trends that would not be recognizable by conventional methods. For energy suppliers, this means the ability to predict the energy requirement and to adapt the offer with unprecedented accuracy, which ensures efficient use of resources and the stability of energy laws.
The ability to analyze complex data records has also made AI the perfect technology to scrub data of inaccuracies. In order to work effectively, however, it must be trained correctly so that it understands that the same data field can be described in various databases, sample surname, family name or second name. Therefore, energy suppliers have to concentrate on the implementation of a robust data governance frameworks of off to maintain data integrity, reduce noise and avoid distortions that could distort AI analyzes and decisions below.
Since the AI ​​continues to penetrate throughout the industry, the future looks bright. The technology is not only used effectively to clean up poor data, but is also used to improve customer service, since increasingly sophisticated chatbots and smooth onboarding are used by accelerating the credit test process.
We turn a corner
Unfortunately, poor data and inconsistent data management practices hinder the progress of the industry in the direction of an environmentally friendly future. Never before, there was a need for precise and reliable data from energy generation to the final consumption. As a rule, challenges have occurred from the data that were either fragmented or if the systems used to collect the data were not able to finish. At a time when the data regulations have become increasingly stricter and potentially crippled fines for non -compliance with fines have reached, it is not time to take risks.
The good news is that we bend around a corner. The technology has significantly contributed to reducing poor data to penetrate the data chain and alleviate the effect if any network should carry through the network. AI, ML and the Internet of Things (IoT) have all re -shaped the landscape of energy management. Their integration in the entire energy sector means a decisive shift to more complex and reliable data processing mechanisms, which is of essential importance for the effective management of renewable energy resources.
However, this does not mean that people should be completely removed from the process. In my opinion, there should always be a human layer for an important business process. Automation is certainly important. However, there will always be nuances within the data as only one person can interpret correctly.