List of Big Data products

  • classification:Big Data

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Since the construction-generated soil will be recycled on-site, the disposal costs for leftover soil and the costs for new purchases will be significantly reduced. 【Disaster Prevention】

  • Special Construction Method

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The Noto Reconstruction Office of the Ministry of Land, Infrastructure, Transport and Tourism has featured our 3D printer in the Nikkei newspaper.

The official X account of the Noto Reconstruction Office of the Ministry of Land, Infrastructure, Transport and Tourism and the Nihon Keizai Shimbun have published that our 3D printer has been adopted for the reconstruction of Noto. The official X account of the Noto Reconstruction Office introduces the use of our products in the restoration work of the Noto Expressway. Additionally, the Nihon Keizai Shimbun mentions that structures made with our products are being used for the restoration of roads damaged by the Noto Peninsula earthquake, and that the construction period can be shortened by about two weeks, so please take a look.

Contributing to the second stage of public infrastructure! Bringing public infrastructure development to the ground. A robust outdoor storage tank for hazardous materials capable of responding to the ...

  • Water Treatment

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Information sharing and work efficiency / Paperless and cost reduction / Filing and electronic documentation

  • Big Data

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The IT infrastructure provided by S&I is the very "foundation" that drives business growth!

  • Big Data
  • IoT

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Bring the technology used by large corporations and government agencies in Japan to your business as well.

  • Firewall
  • Big Data

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3D HP service for multilingual voice

  • others
  • Big Data
  • IoT

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You can utilize it for identifying the characteristics of high performers and improving talent placement matching.

  • Big Data

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We provide hybrid data management that is friendly to both engineers and marketers.

  • Database
  • Big Data

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Socialware that brings innovation to businesses!

  • Big Data
  • others

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Leave device development, casing design, and application development to us.

  • Big Data
  • others

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Leave your website construction needs to us!

  • others
  • Big Data

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As long as you have the data prepared, you can automatically perform advanced predictive analysis with just a few clicks without needing specialized skills.

  • IoT
  • Big Data
  • BI Tools

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"Connecting data to action" Valuable information We weave the story of business Visualizing all data related to people and things.

  • BI Tools
  • IoT
  • Big Data

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Next-generation surgical systems and healthcare management utilizing AI and big data.

  • Big Data
  • Welfare and medical equipment
  • WEB customer service system

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Software developed for latent class analysis. It features an easy-to-use interface that can be operated with a mouse.

  • Big Data
  • Traffic flow analysis system
  • Other Software

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Announcement of the "Latent Class Analysis" seminar to learn analytical methods required in the era of big data <Held on 11/27>

【Due to popular demand, this event has ended】 We will hold a seminar on "Latent Class Analysis," one of the data analysis methods that has been gaining attention in recent years. Latent Class Analysis is an analytical method that seeks hidden commonalities from observed phenomena and classifies them, possessing aspects similar to cluster analysis and factor analysis. It has garnered significant attention as an analytical method needed in the era of healthcare and big data. The seminar program is structured to deepen understanding, covering the history of latent class analysis, explanations of the analytical method, differences from other analytical methods, explanations using case studies, and practical exercises using software for latent class analysis. 【Seminar Program】 1) Why Latent Class Analysis now? The history of Latent Class Analysis 2) Differences from cluster analysis 3) About latent class models: factor analysis meanings, etc. 4) Analysis using latent class analysis software 5) Advanced analysis Utilization of attribution probabilities, utilization of covariates 6) Q&A session

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