Limits of Manual Operations: Complexity of Data Structures and Maintenance Burden

[Free Provision of Explanatory Materials] Transition to automatic updates using external tools in response to the vast amount of data.

last updated Jun 04, 2026

Resolution of User vs. Administrator Conflict: A Management System that Meets Both Parties' Needs

Bridging the gap between the field that wants to analyze freely and the information system that wants centralized management.

last updated Jun 04, 2026

Rapid evolution of data infrastructure through agile development.

[Free Presentation of Explanatory Materials] Repeated improvements in a short cycle, responding promptly to changes in needs.

last updated Jun 04, 2026

The Importance of Data Modeling: Guidelines to Prevent Inconsistencies in Advance

Not just ending with mere "accumulation." Building a foundation for advanced utilization directly linked to business.

last updated Jun 04, 2026

Benefits of using ETL tools: Data integration and reduction of operational burden.

Free presentation of explanatory materials: Integrating data from multiple systems with different formats consistently.

last updated Jun 04, 2026

Metadata Management: The Core of Information that Unleashes the True Value of Data Utilization

Organize 'data about data' to ensure reliability and correctness of interpretation.

last updated Jun 04, 2026

Differentiating between business metadata and technical metadata.

[Free Presentation of Explanatory Materials] Clearly define the purpose and structure. Support the consistency between systems with technology.

last updated Jun 04, 2026

Selection of Metadata Management Tools: From Databricks to AWS

[Free explanatory materials] Prevent the obsolescence of manual management and automatically eliminate information silos.

last updated Jun 04, 2026

Semantic Layer: Preventing discrepancies in data definitions between departments.

No need for specialized SQL. Building an environment where you can directly access data using business terminology.

last updated Jun 04, 2026

Establishment of Data Governance Basic Policy: The Foundation for Safe AI Implementation

From access control to log management. Design guidelines to minimize information leakage risks.

last updated Jun 04, 2026

Conditions for the next-generation data infrastructure: real-time capability and semantic connectivity.

[Free Presentation of Explanatory Materials] Enables interactive collaboration with AI, achieving high-accuracy output.

last updated Jun 04, 2026

The first step of AI transformation: Inventory of existing data infrastructure and understanding the current situation.

[Free explanatory materials] The source of competitiveness lies not in the number of AI implementations, but in the "quality of data."

last updated Jun 04, 2026

Data infrastructure construction: Databricks × Fivetran partnership

[Free Presentation of Explanatory Materials] Professionals Support the Latest Data Lakehouse Design and Implementation

last updated Jun 04, 2026

Example: Introduction of Azure Databricks in the manufacturing industry

[Free Distribution of Explanatory Materials] Automating Failure Prediction and Condition-Based Maintenance Using IoT Data

last updated Jun 04, 2026

Data utilization consultation desk: Leading to solutions for challenges in manufacturing industry DX.

[Free explanatory materials] From inventorying existing data to AI implementation, feel free to consult with us first.

last updated Jun 04, 2026

Example: IT strategy that reduced data preparation time by 80% (free materials provided)

Eliminating data silos with Databricks implementation, achieving self-service utilization for over 300 people.

last updated Jun 04, 2026