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  6. Three reasons why data management is important in a chemical company.

Three reasons why data management is important in a chemical company.

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last updated:Dec 18, 2024

POLYMERIZE ポリマライズ日本法人
POLYMERIZE ポリマライズ日本法人
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Here are three reasons that emphasize the importance of data management in the chemical industry!

In a digital-first world, data is a valuable asset. By accessing relevant data, organizations can minimize potential errors, establish provisional processes, and respond efficiently to market fluctuations. First, it is necessary to learn about efficient data organization and understand best practices in research data management. Modern life sciences companies are beginning to leverage technology for experimental data management. *For more details, you can view the related links. Please feel free to contact us for more information.*

    Document and Data Management
化学薬品会社でデータ管理が重要である3つの理由.PNG

Three reasons why data management is important in a chemical company.

化学薬品会社でデータ管理が重要である3つの理由.PNG
化学薬品会社でデータ管理が重要である3つの理由.PNG
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Introduction of a case study on the efficiency and shortening of the development process for high-performance elastomer seals using AI predictions.

Introduction of a case study on the efficiency and shortening of the development process for high-performance elastomer seals using AI predictions.

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Polymerization Comprehensive Service Guide

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POLYMERIZE

POLYMERIZE ポリマライズ日本法人

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Our company provides a materials informatics platform, PolymerizeLabs, and consulting services for the chemical and materials industries. PolymerizeLabs reflects the unique R&D processes and expertise specific to materials development, enabling seamless data management and AI utilization without the need for programming knowledge. It is the only all-in-one materials informatics platform in the industry that ensures AI prediction accuracy even with limited or sparse data. Based on a data management infrastructure specialized in organizing various materials development data and a highly flexible AI engine equipped with a diverse range of machine learning algorithms, we offer data-driven development processes across various materials fields. We contribute to addressing resource shortages, high cost structures, compliance with environmental regulations, alleviating supply chain bottlenecks, and responding quickly to market changes faced by all R&D departments, thereby enhancing corporate competitiveness and establishing a new standard for R&D processes in the AI era.

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