Open Source Data Analytics Tools
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Data Analytics Tools
View 267 business solutionsBrowse free open source Data Analytics tools and projects below. Use the toggles on the left to filter open source Data Analytics tools by OS, license, language, programming language, and project status.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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PySchool
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4... -
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Kapacitor
Open source framework for processing, monitoring, and alerting
Open source framework for processing, monitoring, and alerting on time series data. Kapacitor is a real-time data processing engine for monitoring and alerting, specifically designed to work with time-series data from InfluxDB. -
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Bdash
Simple SQL Client for lightweight data analysis
Simple SQL Client for lightweight data analysis. You can share the result with gist. Supports MySQL, PostgreSQL (Amazon Redshift), SQLite3, Google BigQuery, Treasure Data, Amazon Athena. You can download and install from Web Site or Releases. -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. There is no installation or configure step needed before you can use the library. All operating system specific code is isolated inside the OS abstraction layers which are kept as small as possible. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Dash
Build beautiful web-based analytic apps, no JavaScript required
Dash is a Python framework for building beautiful analytical web applications without any JavaScript. Built on top of Plotly.js, React and Flask, Dash easily achieves what an entire team of designers and engineers normally would. It ties modern UI controls and displays such as dropdown menus, sliders and graphs directly to your analytical Python code, and creates exceptional, interactive analytics apps. Dash apps are very lightweight, requiring only a limited number of lines of Python or R code; and every aesthetic element can be customized and rendered in the web. It’s also not just for dashboards. You have full control over the look and feel of your apps, so you can style them to look any way you want. -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks. -
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Blue Whale Configuration Platform
Blue Whale smart cloud configuration platform
Has accumulated experience in supporting hundreds of Tencent businesses, compatible with various complex system architectures, born in operation and maintenance, and proficient in operation and maintenance. From configuration management to job execution, task scheduling and monitoring self-healing, and then through operation and maintenance big data analysis to assist operational decision-making, it covers the full-cycle assurance management of business operations in a comprehensive manner. The open PaaS has a powerful development framework and scheduling engine, as well as a complete operation and maintenance development training system, which helps the rapid transformation and upgrading of operation and maintenance. Through the Blue Whale intelligent cloud system, it can help enterprises quickly realize the automation of basic operation and maintenance services, thereby accelerating the transformation of DevOps, realizing a tool culture, and maximizing operational efficiency. -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++ Libraries for 15+ years and deployed it in millions of devices. Create software for connected embedded devices running Linux, Windows Embedded or QNX. Create cross-platform backends in C++ for iOS and Android applications and combine it with a native or HTML5-based user interface. Create software for IoT devices that talk to cloud backends over HTTP REST APIs. See macchina.io for an IoT platform built with POCO. -
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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to expand its capabilities, focusing on versatile data extraction, platform support, and seamless integration with various systems. DocWire SDK is dedicated to streamlining data processing, reducing development time and costs, and harnessing the potential of AI. Its advancements promise a superior experience compared to its predecessor, DocToText. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Command line encryption tool for one time, daemon, or stream data processing. Data stats, check sums, conversion to/from text. Data/keys from files, pipes, standard input. In-place/diverted processing or data-analysis-only. Random, file, password keys.
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neural network designer
a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...
This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application). It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,... -
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TSA_CRAFT
Automatic command line tool for TSA data analysis
DSF is a high-throughput platform of TSA assay to screen various conditions that affect protein stability. To facilitate TSA data analysis, we developed an automatic tool "TSA-CRAFT". TSA-CRAFT was developed by integrating PERL script and Gnuplot. PERL scripts manage the entire workflow and data processing procedures of TSA data analysis. On the other hand, Gnuplot takes over the curve fitting and result presentation works. All analysed results are coded in an html file that can be easily displayed by a web browser. -
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Amazon Kinesis Flink Connectors
Contains various Apache Flink connectors to connect to AWS data
This library contains various Apache Flink connectors to connect to AWS data sources and sinks. This repository contains various Apache Flink connectors to connect to AWS Kinesis data sources and sinks. Flink maintain backwards compatibility for the Sink interface used by the Firehose Producer. This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. An Apache Flink application is a Java or Scala application that is created with the Apache Flink framework. You author and build your Apache Flink application locally. Applications primarily use either the DataStream API or the Table API. The other Apache Flink APIs are also available for you to use, but they are less commonly used in building streaming applications. The Apache Flink DataStream API programming model is based on two components. -
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Apache InLong
Apache InLong - a one-stop integration framework for massive data
Apache InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. InLong (应龙) is a divine beast in Chinese mythology who guides the river into the sea, and it is regarded as a metaphor of the InLong system for reporting data streams. InLong was originally built at Tencent, which has served online businesses for more than 8 years, to support massive data (data scale of more than 80 trillion pieces of data per day) reporting services in big data scenarios. The entire platform has integrated 5 modules: Ingestion, Convergence, Caching, Sorting, and Management, so that the business only needs to provide data sources, data service quality, data landing clusters and data landing formats. -
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CANStream
An applicaton for CAN bus coms development, testing and validation
CANStream is a .NET application intended to be used for CAN (Controller Area Network) bus communication development, testing and validation. CANStream allows to extensively test any system using CAN communication by sending and receiving CAN frames. Thanks to its powerful built-in mathematical expression evaluator, CANStream can also behave as a real control system feeding back the test device or commanding a third party device with context sensible data. Extended data logging and data analysis features of CANStream provide a comprehensive solution for testing and results analysis CANStream extensively uses the PCAN-Basic API developed by PEAK System for the PCAN-USB adapter You will therefore need to have PCAN-USB adapter and at least one free USB port available to make a complete use of CANStream. CANStream can manage up to eight PCAN-USB adapters at the same time, thus you will need eight USB ports available. -
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CSI-Math-Notation-PostfixInfix
Perl Lib Math Notation
* Introduction: - This Module is a Library based Perl code. - The library provide: - Convert INFIX expressions to POSTFIX; - Convert POSTFIX expressions to INFIX and; - Perform POSTFIX context validations. - Context validation can be implemented in item selection routines or data context validation, when it is possible to identify data to be selected or ignored in some data analysis process. * NOTE: - Before any implementation, we recommend details in WIKI (https://sourceforge.net/p/csi-math-notation-postfixinfix/wiki/) or the CPAN Perl Modules, see: https://metacpan.org/pod/Math::Notation::PostfixInfix * Support: The Support Service is FREE. Do you need support? Open a ticket and I will get back to you as soon as possible. * Professional Services: Do you need any FREE professional services to use? Open a ticket as "FAQ request" and I will get back to you as soon as possible. i.e: subject: -
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Qt4 GUI for scientific data analysis and visualization using Matlab (tm) style syntax. Link together Qt projects and other C++ libraries in an integrated user interface. For more information, visit: http://groups.google.com/group/chainlink
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ECharts
A powerful, interactive charting and visualization library for browser
ECharts is a free and open source charting and visualization library that gives you an easy way to add interactive, intuitive, custom charts to your commercial products, projects, presentations and more. It offers a rich set of features that includes rendering ability for ten-million-level data, Wechart and Powerpoint support, multi-dimension data analysis, and more. It also has a number of extensions for various applications. ECharts is written in pure JavaScript, and is based on zrender, a new and lightweight canvas library. -
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GNUexp is a GNUstep/Cocoa framework and a collection of tools helping you to plan, develop, and administer applications associated with visual psychophysics, experimental psychology and statistical data analysis.
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HEIMDALL
High-End Interface for Monitoring & spatial Data Analysis using L2Norm
HEIMDALL, short for High-End Interface for Monitoring and spatial Data Analysis using L2-Norm, is a set of public libraries written in JAVA which contains routines and algorithms for geodetic hardware connection. To observe objects (in general spatial points) continuous, HEIMDALL’s programmable logic arrays can be used to design monitoring systems. For data analysis an interface to the least-squares program JAG3D can be provided. The serial communication with e.g. inclination sensors, meteorological stations or total stations is handled by the library RXTX. If only a proprietary communication via dynamic-link library (dll are not shared by the project) is supported by the devices, JNA is resorted. Notice, HEIMDALL is not a stand-alone monitoring application. It is only a set of libraries. -
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Logbus-ng consists in a set of tools to aid developers perform Log Analysis in all the stages: log generation, collection, distribution, storage and analysis. It is designed specifically for Field Failure Data Analysis in critical distributed systems
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MS-Helios
MS-Helios: A Circos wrapper to visualize multi-omic datasets
Advances in high-resolution mass spectrometry facilitate the identification of hundreds of metabolites, thousands of proteins and their post-translational modifications. This remarkable progress poses a challenge to data analysis and visualization, requiring methods to reduce dimensionality and represent the data in a compact way. To provide a more holistic view, we recently introduced circular proteome maps (CPMs). However, the CPM construction requires prior data transformation and extensive knowledge of the Perl-based tool, Circos. We present MS-Helios, an easy to use command line tool with multiple built-in data processing functions, allowing non-expert users to construct CPMs or in general terms circular plots with a non-genomic basis. MS-Helios automatically generates data and configuration files to create high quality and publishable circular plots with Circos. -
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ModuleFair is a generic, module-based framework upon which to quickly build anything from data analysis programs to game level editors. This project is no longer maintained.
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PANDA
A comprehensive and flexible quantification tool for proteomics data
PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels of spectra, peptides and proteins, PANDA works out a few quantitative filters and new scores for quantification confidence. Third, PANDA is designed for processing proteomics big data in parallel. -
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PINCIS
PINCIS.pl is a Perl bioinf. script to analyze PICS data
PINCIS.pl (PIcs N-/C-terminal Inferred Substrates perl script) is a small, command line tool to designate and analyze PICS (Schilling et al., Nat. Protocols, 2011) data to gain the prime and non-prime site specificity of proteases. Thus, the script filters given peptide lists for library peptides (generated by the digestion protease in the proteomics workflow rather then the protease of interest) and prints out lists of inferred N- and C-terminal cleavage window extensions which can be concurrently used to generate cleavage specificity visualizations like the iceLogo (https://iomics.ugent.be/icelogoserver/create).
