About Data Business

We have four business areas and provide consistent services and consulting services based on specialized knowledge and experience based one by developing specialized business in those areas and  complementing and synergizing each of them.  Also, we provide BtoB and BtoG business supports by engaging in specific businesses and operations either separately or in collaboration/partnership.

Furthermore, we are of a research and development company and provide Proof of Concept (POC) supports such as interdisciplinary ones, commercialization and social implementation.

Because of increase of Internet usage and penetration of the Internet of Things (Iot) in many fields, the generation, the collection and the accumulation of large amounts of Big Data is made exponentially.

Under such circumstances, data have long been said to be the resources of the 21st century, and not only the amount of data, but also the quality including the abundance of its types, processing speed and the accuracy is important in order to improve the accuracy of AI analysis and generate value and profit.

We follow various problems in data utilization, build a data-driven society, create evidence to support decision making, and so engage in data science consulting work that has a positive impact on customer profits and business progress.

Clients：

・ Government offices, Public institutions, Local governments

・ Corporations/Private companies

・ Research /educational institutions

・ Individuals

Business areas：

• Real estate, architecture, city planning, regional planning                                                              
• Transportation, MaaS
• Wide range of space fields
• Environmental energy (saving, construction, creation / reconstruction, etc.), smart city, smart building, smart home, smart community, energy management,
• Digital Twin, Compact City, Super City
• Climate change, Ris Tech, environmental protection, meteorological data utilization, sustainable development
• Infrastructure / construction
• Disaster prevention / mitigation, natural disaster countermeasures
• Service engineering (commercial, logistics, supply chain, consumer trend survey)
• Finance and IT data mining {SDG, ESG related, risk countermeasures, economic& financial indicators(financial or non financial information, TCFD support)}
• Medical data, medical facility operation management, UX. (User experience), PX (Patient-Centered Primary Care)
• Material informatics (Eco products, Sustainable products, Resilient products)                     etc

Service to offer:

Data Science Buisiness Liaison& Solution Partner unit(DSBL&SPU)

• Data science, AI, Big data analysis, code creation (R, Python, SQL, Visual basic, etc.) 　　　　　　　　　　　　　Data-driven, Data use business supportRequirement clarification, design / development, testing, maintenance operation, POS, in-house production support  Fieldwork, Data acquisition support, etc. 
• General Data science business ・ Data analysis　　　　　　　　　　　　　　　　　　　　　　　　　　　　
• Data visualization-Statistical analysis (Basic statistics, Multivariate analysis, data mining, machine learning, Deep learning, reinforcement learning, etc.) using CRISP-DM, Agile or cycle approach, Waterfall Project management.                                                                    　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　
• Business consulting through Data science work par target business 　　　　　　　　　　　　　　　　　　　　　　　　　
• Analysis and prediction of geospatial information and meteorological / environmental / climate information data
• Image recognition and image analysis
• 2D, 3D maps and Digital twin
• Data visualization, analysis and service engineering that integrates customer information, behaviour observation information, purchase information, regional information, social / economic information etc into spatial and environmental information.
• Survey and inspection in infrastructure and manufacturing ・Specific environmental / social / hygiene / health-conscious tasks in SDG / ESG investment etc.

Cross-industry standard process for data mining (CRISP-DM) development:

1) Understanding of the business, customer concepts and requirements → 2) Clarification of objectives and project plans → 3) Analysis and verification of data collection and data input, confirmation and determination of data used → 4) Data preparation, (data cleaning) And data set preparation) → 5) Data modeling (selection of optimal data and algorithm, trial, modeling, parameter setting → 6) Result verification, resetting of conditions and parameters → verification of business plan and verification results, process review Developing a response plan → 7) Developing a deployment plan, maintaining, formulating an operation plan, and formulating a final report

Waterfall development:

1) Organization of the concepts and conditions → 2) Design → 3) Design execution → 4) Data and output check and verification → 5) Deployment and demonstration

Agile or cycle approach development:

1) Understanding of the business plan → 2) Understanding of the data → 3) Data preparation and development → 4) Modeling → 5) Assessment → 6) Deployment → Implementation as a series of loops

Data Utilization Business

Use cases of Data Utilization Business(Weather data drive)