Showing 4 open source projects for "python data analysis"

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  • Securden Privileged Account Manager Icon
    Securden Privileged Account Manager

    Unified Privileged Access Management

    Discover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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  • SoftCo: Enterprise Invoice and P2P Automation Software Icon
    SoftCo: Enterprise Invoice and P2P Automation Software

    For companies that process over 20,000 invoices per year

    SoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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  • 1
    IoTDB

    IoTDB

    Apache IoTDB

    Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. ...
    Downloads: 11 This Week
    Last Update:
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  • 2
    DEVS-Suite Simulator

    DEVS-Suite Simulator

    Component, CA, and CCA models; superdense time, DB repo, testing, etc.

    Integrated component-based and cellular automata (CA) Parallel DEVS simulator: https://acims.asu.edu/devs-suite/ OFFERS: 1) synchronized execution & animation, 2) run-time linear/superdense I/O & state trajectories, 3) Action Level Real-Time modeling & simulation, 4) model checking, 5) ABM, 6) CA & composable CA playback, 7) KIB interaction modeling, 8) hierarchical model libraries, 9) Black-Box testing & debugging, 10) PostgreSQL repository, 11) FMU (OpenModelica), 12) OSATE (AADL)...
    Downloads: 19 This Week
    Last Update:
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  • 3
    GROWbox Supervisor System (GROWSS)

    GROWbox Supervisor System (GROWSS)

    Automated Plant Environment Growing System using Raspberry Pi

    GROWbox Supervisor System (GROWSS) is a grow box or grow cabinet environmental controller. GROWSS uses a Raspberry Pi (RPI) & Grove sensors to monitor and control the environment in your grow box or cabinet. Environmental factors such as temperature, humidity, soil moisture, & smoke (from fire) are monitored and displayed on a terminal connected to the RPI & on a mobile app. GROWSS also controls the exhaust fan and grow lights based on the time interval (ie. 12 hours on/12 hours off) &...
    Downloads: 1 This Week
    Last Update:
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  • 4
    GreenHop

    GreenHop

    Energy and environmental monitoring of the server room

    The solution GreenHop aims to perform energy and environmental (temperature, humidity, dew point and atmospheric pressure) monitoring of the Data Center server room, providing energy efficiency indicators through green metrics for Data Centers. The GreenHop solution is based on open source software and hardware. The approach of using open source solutions enables its deployment easier and independently of suppliers at the same time makes the solution scalable to the needs of each...
    Downloads: 0 This Week
    Last Update:
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  • The full-stack observability platform that protects your dataLayer, tags and conversion data Icon
    The full-stack observability platform that protects your dataLayer, tags and conversion data

    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

    Code-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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