Nowcast Supports Fine Today in Building a Next-Generation Data Analytics Platform
Nowcast has assisted Fine Today in constructing a modern data analytics platform using Snowflake and dbt to accelerate data-driven management and optimize supply chains.
📋 Article Processing Timeline
- 📰 Published: March 30, 2026 at 20:00
- 🔍 Collected: March 30, 2026 at 22:56 (2h 55m after Published)
- 🤖 AI Analyzed: April 22, 2026 at 04:53 (533h 57m after Collected)
Nowcast Inc. (Headquarters: Chiyoda-ku, Tokyo; Representative Director and CEO: Hitoshi Tsujinaka, hereinafter "Nowcast"), a Finatext Group company that realizes embedded finance by providing next-generation financial infrastructure, has supported Fine Today Co., Ltd. (Headquarters: Minato-ku, Tokyo; Representative Director, President & CEO: Tetsuo Komori, hereinafter "Fine Today") in building a next-generation data analytics platform utilizing Snowflake and dbt to accelerate company-wide data-driven management.
Through this support, Fine Today has established an environment where core data such as supply chain and financial accounting can be managed and utilized in an integrated manner.
■ Background
Fine Today is a personal care company that develops brands such as "TSUBAKI," "SENKA," and "uno." While promoting the use of data to optimize the entire value chain from production to sales, the company faced the following challenges:
- Black-boxing and Personalization of Data Pipelines
In the conventional data infrastructure, complex business logic was fixed within programs, and the data structure was not optimized for each analytical perspective (dimension). This required a massive amount of man-hours for data reuse, quality control, and modification, hindering rapid data utilization.
- Lack of Data Governance
There was a lack of catalog functions to manage the location and definition of data, making it difficult for developers and users to access necessary data. Furthermore, there was a need to strengthen the control of authority and resource management in the production and verification environments.
- Needs for Advanced Data Utilization
With the conventional data infrastructure structure, it was difficult to analyze data based on indicators and analytical axes integrated and controlled across the group globally, and it could not be fully utilized for management strategies and policy considerations. As a result, rapid and flexible decision-making was hindered, cross-sectional use and reuse of data were limited, and advanced analysis utilizing AI models was difficult to realize.
■ Overview of Support
Nowcast provided comprehensive support, not just system construction, but from architecture design and implementation to formulating operational rules and transferring skills to internal engineers.
1. Reconstructing Dimensional Models with Snowflake x dbt
Snowflake was adopted for the data warehouse (DWH) and dbt for data transformation, reconstructing complex supply chain and financial data into a dimensional model organized by business axes such as "product," "customer," and "time." As a result, complex processing logic was visualized on an SQL basis, realizing an environment where anyone can handle data with the same definition.
2. Infrastructure as Code (IaC) and Strengthening Governance with Terraform
Infrastructure settings for AWS and Snowflake were codified using Terraform (IaC: Infrastructure as Code). This automated environment construction, prevented configuration errors, and enabled strict authority management and audit log tracking, realizing enterprise-level governance.
Through this support, Fine Today has established an environment where core data such as supply chain and financial accounting can be managed and utilized in an integrated manner.
■ Background
Fine Today is a personal care company that develops brands such as "TSUBAKI," "SENKA," and "uno." While promoting the use of data to optimize the entire value chain from production to sales, the company faced the following challenges:
- Black-boxing and Personalization of Data Pipelines
In the conventional data infrastructure, complex business logic was fixed within programs, and the data structure was not optimized for each analytical perspective (dimension). This required a massive amount of man-hours for data reuse, quality control, and modification, hindering rapid data utilization.
- Lack of Data Governance
There was a lack of catalog functions to manage the location and definition of data, making it difficult for developers and users to access necessary data. Furthermore, there was a need to strengthen the control of authority and resource management in the production and verification environments.
- Needs for Advanced Data Utilization
With the conventional data infrastructure structure, it was difficult to analyze data based on indicators and analytical axes integrated and controlled across the group globally, and it could not be fully utilized for management strategies and policy considerations. As a result, rapid and flexible decision-making was hindered, cross-sectional use and reuse of data were limited, and advanced analysis utilizing AI models was difficult to realize.
■ Overview of Support
Nowcast provided comprehensive support, not just system construction, but from architecture design and implementation to formulating operational rules and transferring skills to internal engineers.
1. Reconstructing Dimensional Models with Snowflake x dbt
Snowflake was adopted for the data warehouse (DWH) and dbt for data transformation, reconstructing complex supply chain and financial data into a dimensional model organized by business axes such as "product," "customer," and "time." As a result, complex processing logic was visualized on an SQL basis, realizing an environment where anyone can handle data with the same definition.
2. Infrastructure as Code (IaC) and Strengthening Governance with Terraform
Infrastructure settings for AWS and Snowflake were codified using Terraform (IaC: Infrastructure as Code). This automated environment construction, prevented configuration errors, and enabled strict authority management and audit log tracking, realizing enterprise-level governance.