i-STREAM is an all-in-one data analytics solution that supports the entire data analysis process, from data extraction to visualization.

It offers a wide range of functions, including ETL (Extract, Transform, Load), heterogeneous data integrated analysis, data mining, statistical analysis, and predictive analytics. With its user-friendly and intuitive interface, i-STREAM enables users to efficiently handle complex data processing requirements. Additionally, data scientists can leverage advanced AI and statistical algorithms such as Artificial Neural Networks (ANN), Deep Neural Networks (DNN), and Convolutional Neural Networks (CNN) to professionally process data. i-STREAM can be utilized as a predictive analytics tool across various industries.

Functions

Interface

Analyzes the user's natural language queries and transforms the natural language into a structure that the meta engine can understand.

Functions

  • Multiple Data Source
Access / Integration

    • Provides robust input/output processing capabilities to seamlessly handle heterogeneous database.
    • Enables unified processing and utilization of data from various sources.

  • Data Preprocessing

    • Offers a flexible data processing environment.
    • Simplifies complex data handling through data preprocessing functions.

  • Statistical & Predictive
Analytics

    • Supports univariate and multivariate analysis techniques.
    • Provides descriptive, inferential, and predictive statistical methods.
    • Allows the integration of proprietary algorithms developed by client organizations.

  • Big Data Analytics

    • Employs in-memory technology for efficient big data mining.
    • Optimizes computational processes through caching.
    • Delivers superior performance for big data analysis with multi-processing capabilities.

  • Machine Learning /
AI

    • Supports scripting tools like Python and R.
    • Integrates Python libraries such as pandas, numpy, scikit-learn, and TensorFlow for advanced analytics.
    • Offers a variety of AI algorithms to enhance data analysis capabilities.

  • Visualization/BI

    • Includes visualization nodes for immediate representation of analytical results.
    • Supports integration with OLAP and dashboards for seamless report development.

Features

  • Enables quickly and easily processing of all analytical stages, from data extraction to visualization, UI-based interface.
  • Simplifies usage for non-experts, expanding accessibility to a broader audience, including business users (Citizen Data Scientists) in addition to data scientists.
  • Allows the visualization and deployment of big data analytical models within a user-friendly workflow interface.
  • Provides a wide range of algorithms in a modular format, enabling users to drag-and-drop for immediate application in analysis.
  • Facilitates easy visualization of results using diverse analytical algorithms.
  • Supports the integration of TensorFlow, R algorithms, and proprietary client algorithms for versatile and advanced analytics.

Architecture

Architecture

Processing

Applications

Field of application

Benefits

  • Contribute to the widespread adoption of evidence-based decision-making trends over intuition across society.
  • Highlight the growing strategic necessity in national and industrial contexts, with applications in areas such as combat modeling, particular matter management, epidemic response, and reduction of delinquency rates, leveraging big data analysis across various public institutions.

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