Our goal "Deep learning solutions"

Machine learning (deep learning) is one of the technological elements that have dramatically developed the current third-generation AI, and an essential part of utilizing AI and machine learning is the maintenance of data, known as teacher data or training data.
Data warehousing (DWH) has been traditionally used for retaining and utilizing data. In this method, the goal of data utilization is set in the form of outputs (statistical data, graphs, forms, etc.) designed in advance for the business, and data are stored in the appropriate format and items by working backwards from the required data form.
However, this method stores data in a way that is only optimized for a specific extraction style and a specific analysis algorithm; and the data needs to be reorganized and stored again if it is to be used in a different way. Therefore, when introducing AI and deep learning, instead of storing data in a form that depends on specific analysis algorithms or statistical tools, it is desirable to store data in the form of "data lake," where the data is stored in the same form as when it was generated and can be retrieved as needed when the various algorithms and tools including AI are modified.

Safe, easy, and fast implementation from data accumulation to generation of learning results