You have data available, but don’t know how to use it. You don’t have staff who can analyze the data. You want to carry out marketing activities based on data. VIETIS will help you solve “ Increasing sales” , “Expanding profit” and “Making speedy decisions”.
We perform market research and analyze business/ business flows to identify issues. After further classifying and prioritizing the extracted issues, we will collect sample data.
This is the process of creating a data model in order to clarify data requirements and determine the implementation range. Start with simple machine learning, verify performance, and decide which model to use.
We will introduce a system that automates the process of data collection and data preprocessing, as well as management tools for verifying and evaluating the results. At the same time, we will change the algorithm and build an environment that optimizes machine learning to improve the accuracy of data analysis.
Analyze about 20,000 DATA flights and establish aviation fuel-saving solution
The client spent about 77 billion yen on fuel costs in 2017. This accounts for 26.5% of total spending. In this project, we aimed to devise and implement a fuel-saving solution by data analysis.
Fuel costs are affected by a variety of factors, including aircraft design, flight mode, load weight, and fuel volume.
The project team analyzed data from about 20,000 A350 aircraft for the two years 2017-2019, provided by many systems such as CFP, ACAR, and LOOMS.
As a result of data analysis, it was discovered that there was a discrepancy between the amount of fuel required by the captain before the flight and the actual amount of consumption. As a result of changing the guidelines to require declaration when the fuel of 500 liters or more is required, almost no captain demands a fuel amount of 500 liters or more, and we succeeded in saving a lot of fuel.