AES
AES Brasil is a subsidiary of AES Corporation, one of the largest energy companies in the United States. Its segment has been present in Brazil since 1997, and is responsible for operating in the sectors of services, generation, and storage of electrical energy.
Desafio de negócio
Business challenge
To handle more than 30TB of internal data, we implemented advanced technical solutions, including algorithms such as Hillclimbing, Genetic, and geographic K-means. These approaches allowed for in-depth and strategic analysis, providing crucial insights that contributed to the significant success of this project. The main objective was to determine the best location for AES Eletropaulo's operational bases, and with Khipo's expertise, the project resulted in impressive savings of R$120 million for the company.
Solução
Solution
Khipo is pleased to share an extraordinary Data Science success story: the analysis of Eletropaulo's fleet, which resulted in significant improvements, avoided idleness, and reduced operational costs. This project was divided into three crucial phases: Base Preparation and Analysis, Descriptive Analysis of Data, and Opportunities. The analysis allowed Eletropaulo to select properties for sale and increase the efficiency of existing bases.
Resultados
Project conclusion
To handle more than 30TB of internal data, we implemented advanced technical solutions, including algorithms such as Hillclimbing, Genetic, and geographic K-means. These approaches allowed for in-depth and strategic analysis, providing crucial insights that contributed to the significant success of this project. The main objective was to determine the best location for AES Eletropaulo's operational bases, and with Khipo's expertise, the project resulted in impressive savings of R$120 million for the company. The main results obtained are the following:
Precise Data Analysis: The technical solutions implemented by Khipo allowed accurate analysis of the data, even considering its large magnitude. This made it possible to extract valuable information from this voluminous data.
Advanced Algorithms: The use of advanced algorithms such as Hillclimbing, Genetic, and Geographic K-means demonstrated Khipo's ability to apply cutting-edge techniques to solve complex data analysis challenges.
Significant Savings: The project led by Khipo had a notable financial impact for AES Eletropaulo, resulting in impressive savings of R$120 million. This is a notable achievement that demonstrates the effectiveness of the implemented approaches.
Strategic Decision Making: The crucial insights obtained through data analysis allowed AES Eletropaulo to make informed strategic decisions about the best location of its operational bases. This contributed to optimizing the company's operations.
Khipo's Expertise: Khipo's expertise played a key role in the success of the project. The company demonstrated its technical knowledge and analytical skills, contributing to the achievement of exceptional results.
In summary, Khipo obtained highly satisfactory results when dealing with the analysis of massive data to determine the best locations of AES Eletropaulo's operational bases. The significant savings achieved demonstrate the positive impact of this advanced approach on the company's strategic decision-making and financial efficiency.
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