This project is a data management system that allows users to centralize, analyze, and generate reports from their data. It is designed to help businesses make informed decisions by providing a clear and organized view of their data.

This project focuses on managing and analyzing data from Godiva devices, providing real-time monitoring, data organization, and visualization tools to optimize the use of Godiva devices.

The sambar-shiny project provides an easy-to-use interface for data visualization and analysis, enabling users to manage, analyze, and present data in a more efficient and collaborative manner. It simplifies the process of creating charts, graphs, and reports, allowing teams to make informed decisions based on data-driven insights.

The excel-result project is designed to help users efficiently analyze, manipulate, and visualize data. By providing a user-friendly interface and streamlined workflows, users can quickly process and generate reports, making data-driven decision-making more accessible and efficient.

CorTexT Corpus List Indexer is a method in CorTexT Manager that allows users to organize and analyze textual data, selecting a field to work on within their dataset and optionally provide a custom list of items to be specifically indexed. Advanced settings enable tagging of documents and controlling how occurrences are counted during indexation.

This project focuses on identifying and analyzing payload characteristics in data transmissions, with the aim of detecting anomalies and optimizing data transfer processes. By using advanced algorithms and techniques, it provides valuable insights to improve the efficiency and security of data transfers.

This project contains the data and code for analyzing raw data and generating figures for the manuscript "Maximizing protein production by keeping cells at optimal secretory stress levels using real-time control approaches" by Sosa-Carrillo and colleagues. The repository is composed of four folders: code, analysis_figures, data, and plasmids. The code makes use of several packages including Pandas, NumPy, SciPy, sklearn, matplotlib, and cma.

BuildUPViewer is a project for visualizing and analyzing building data, allowing users to track the progress of building construction. It uses geospatial data to provide a detailed view of buildings and their evolution over time.

This project contains a Logstash configuration file for processing Open edX tracking logs, anonymizing personal user data in the process. The structured data can then be used for various business purposes such as analyzing user behavior or improving course content.

The slicer project is a tool for processing and managing data from hardware devices. It provides functionalities for analyzing and extracting data, managing device properties, and handling device initialization and deletion.