Nowcast Supports FineToday in Building a Next-Generation Data Analysis Platform
Nowcast, a member of the Finatext Group, has assisted FineToday in constructing a next-generation data analysis platform using Snowflake and dbt. This initiative aims to accelerate data-driven management by integrating supply chain and financial data, overcoming previous challenges related to data silos and governance.
📋 Article Processing Timeline
- 📰 Published: March 30, 2026 at 20:00
- 🔍 Collected: March 30, 2026 at 22:56 (2h 55m after Published)
- 🤖 AI Analyzed: June 2, 2026 at 13:02 (1526h 6m after Collected)
Nowcast, Inc. (Headquarters: Chiyoda-ku, Tokyo; Representative Director and CEO: Hitoshi Tsujinaka; hereinafter "Nowcast"), a member of the Finatext Group that realizes embedded finance through the provision of next-generation financial infrastructure, has supported FineToday Co., Ltd. (Headquarters: Minato-ku, Tokyo; Representative Director, President and CEO: Tetsuro Komori; hereinafter "FineToday") in building a next-generation data analysis platform utilizing Snowflake and dbt to accelerate company-wide data-driven management.
Through this support, FineToday has established an environment capable of integrally managing and utilizing core data, such as supply chain and financial accounting data.
■ Background
FineToday 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-boxed and siloed data pipelines
In the previous data infrastructure, complex business logic was hard-coded into programs, and data structures were not optimized for specific analytical perspectives (dimensions). This required significant man-hours for data reuse, quality control, and modifications, 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 information. Additionally, there was a need for stronger control over permission management and resource management between production and verification environments.
・Needs for advanced data utilization
Under the previous data infrastructure structure, it was difficult to perform data analysis based on integrated and controlled indicators and analytical axes across the group and globally, preventing the data from being fully utilized for management strategy and policy consideration. As a result, rapid and flexible decision-making was hindered, and there were limits to cross-sectional data usage and reuse, making it difficult to implement advanced analysis using AI models.
■ Support Overview
Nowcast provided end-to-end support, ranging from architecture design and implementation to the formulation of operational rules and skill transfer to in-house engineers, rather than merely building a system.
1. Reconstruction of a dimensional model using Snowflake × dbt
By adopting Snowflake for the data warehouse (DWH) and dbt for data transformation, complex supply chain and financial data were reconstructed into a dimensional model organized by business axes such as "product," "customer," and "time." This visualized complex processing logic on an SQL basis, creating an environment where anyone can handle data with consistent definitions.
2. Infrastructure as Code (IaC) using Terraform and enhanced governance
Infrastructure settings for AWS and Snowflake were codified using Terraform (IaC: Infrastructure as Code). This automated environment construction and prevented configuration errors, while enabling strict permission management and audit log tracking, thereby establishing an enterprise-level governance system.
3. Promotion of AI data utilization through the development of a semantic layer
To facilitate intuitive data searching using natural language and the use of generative AI (such as Snowflake Cortex Analyst), support was provided for the development of a semantic layer. This allows analytical axes and business metadata to be managed integrally, creating an environment where business users can easily and accurately extract necessary data through AI.
■ Comment from Mr. Hidehiko Komuro, IT Division, FineToday Co., Ltd.
"Previously, the specifications of our data infrastructure were black-boxed, and it took a lot of time and cost to make modifications or ingest new data. With Nowcast's support, we were able to introduce modern technologies such as dbt and Terraform, transforming it into a highly transparent platform that we can manage and operate ourselves. Moving forward, we will utilize this platform to accelerate business-linked data utilization."
■ Future Outlook
FineToday will continue to promote the sophistication of its data utilization with the newly built platform at its core. Nowcast will continue to strongly support FineToday's DX (Digital Transformation) through both generative AI and data infrastructure.
■ Inquiries regarding Nowcast's Data AI Solutions
Companies interested in this matter or Nowcast's data AI solutions, please inquire via the following link.
Inquiry Form: https://finatext.com/contact
Through this support, FineToday has established an environment capable of integrally managing and utilizing core data, such as supply chain and financial accounting data.
■ Background
FineToday 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-boxed and siloed data pipelines
In the previous data infrastructure, complex business logic was hard-coded into programs, and data structures were not optimized for specific analytical perspectives (dimensions). This required significant man-hours for data reuse, quality control, and modifications, 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 information. Additionally, there was a need for stronger control over permission management and resource management between production and verification environments.
・Needs for advanced data utilization
Under the previous data infrastructure structure, it was difficult to perform data analysis based on integrated and controlled indicators and analytical axes across the group and globally, preventing the data from being fully utilized for management strategy and policy consideration. As a result, rapid and flexible decision-making was hindered, and there were limits to cross-sectional data usage and reuse, making it difficult to implement advanced analysis using AI models.
■ Support Overview
Nowcast provided end-to-end support, ranging from architecture design and implementation to the formulation of operational rules and skill transfer to in-house engineers, rather than merely building a system.
1. Reconstruction of a dimensional model using Snowflake × dbt
By adopting Snowflake for the data warehouse (DWH) and dbt for data transformation, complex supply chain and financial data were reconstructed into a dimensional model organized by business axes such as "product," "customer," and "time." This visualized complex processing logic on an SQL basis, creating an environment where anyone can handle data with consistent definitions.
2. Infrastructure as Code (IaC) using Terraform and enhanced governance
Infrastructure settings for AWS and Snowflake were codified using Terraform (IaC: Infrastructure as Code). This automated environment construction and prevented configuration errors, while enabling strict permission management and audit log tracking, thereby establishing an enterprise-level governance system.
3. Promotion of AI data utilization through the development of a semantic layer
To facilitate intuitive data searching using natural language and the use of generative AI (such as Snowflake Cortex Analyst), support was provided for the development of a semantic layer. This allows analytical axes and business metadata to be managed integrally, creating an environment where business users can easily and accurately extract necessary data through AI.
■ Comment from Mr. Hidehiko Komuro, IT Division, FineToday Co., Ltd.
"Previously, the specifications of our data infrastructure were black-boxed, and it took a lot of time and cost to make modifications or ingest new data. With Nowcast's support, we were able to introduce modern technologies such as dbt and Terraform, transforming it into a highly transparent platform that we can manage and operate ourselves. Moving forward, we will utilize this platform to accelerate business-linked data utilization."
■ Future Outlook
FineToday will continue to promote the sophistication of its data utilization with the newly built platform at its core. Nowcast will continue to strongly support FineToday's DX (Digital Transformation) through both generative AI and data infrastructure.
■ Inquiries regarding Nowcast's Data AI Solutions
Companies interested in this matter or Nowcast's data AI solutions, please inquire via the following link.
Inquiry Form: https://finatext.com/contact