Open Source Windows Data Analytics Tools

Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free. Gephi is an award-winning open-source platform for visualizing and manipulating large graphs. It runs on Windows, Mac OS X and Linux. Localization is available in English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech and German. Fast Powered by a built-in OpenGL engine, Gephi is able to push the envelope with very large networks. Visualize networks up to a million elements. All actions (e.g. layout, filter, drag) run in real-time. Simple Easy to install and get started. An UI that is centered around the visualization. Like Photoshop™ for graphs. Modular Extend Gephi with plug-ins. The architecture is built on top of Apache Netbeans Platform and can be extended or reused easily through well-written APIs.

Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types.

FlowViewer provides a convenient web-based user interface to Mark Fullmer’s flow-tools suite and CMU's netflow data capture/analyzer, SiLK. The inclusion of the underlying SiLK tool set enables FlowViewer users to continue to use the tool with the newer IPFIX netflow data protocol, which includes support for IPv6 and Cisco's v9 and FNF netflow. FlowViewer has been developed for NASA’s Earth Sciences Data and Information System (ESDIS) networks, and credit goes to NASA for their usual outstanding support of innovation. The FlowViewer tools provide additional graphing and tracking features by utilizing open source software including Thomas Boutrell’s gd, Lincoln Stein's GD, Martien Verbruggen's GD::Graph, and Tobias Oetiker’s RRDtool. FlowViewer v4.6 fixes non-UTC local time environments for FlowViewer and FlowGrapher, and $no_devices_or_exporters FlowMonitor_Collector problem. **Note: SiLK must be v3.8.0 or later. Version 3.9 handles sFlow data.

The goal of the Perl OBD-II Logger project is to create a flexible and efficient application that can capture and log OBD-II Mode 0x01 PID data from an automotive scantool. It is designed with accurate and efficient PID data logging in mind, and provides NO support for reading or resetting diagnostic trouble codes. By default, the output log file contains time-stamped PID values in a simple Comma Separated Values (CSV) format that can be readily imported into popular data analysis or spreadsheet applications. (Output to an SQLite3 database file is also available). It is written in Perl, so it runs in any computing environment with a working Perl interpreter. The program supports scantools that are based on the ELM Electronics ELM327 or OBD Solutions STN1110 programmed microcontrollers. It has been tested with scantools using legacy RS-232 serial, serial over USB, and Bluetooth hardware interfaces. Perl OBD-II Logger even runs on the popular Raspberry Pi computer!

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.

FwPlatinum provides real time data analysis of CheckPoint FireWall-1 connection logs. Data is stored for up to 2 years, and is accessed by CGI generated graphs which can drill down to the specific time that you are interested in.

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. In the scene of factories, there are tens of devices under LAN network. IoTDB can be installed on a local controller server in the factory to receive data from those devices. The local controller server (normal PC or workstation) with IoTDB can provide the ability to persist data and query data with SQL-like interface. In addition, with TsFile-Sync tool, TsFiles on the local controller can be transmitted to the data center equipped with IoTDB instance in the cloud.

ROOTSNNS is a set of C++ classes which allows one to use the Stuttgart Neural Network Simulator kernel (ansi-C) within the ROOT, a data analysis package. Multiple ANNs can be built, trained, and tested, while results and ANN performance can be saved.

Savuka global analysis software (www.osmanbilsel.net) is installed and configured in a light version of SliTaz linux (www.SliTaz.org). root name: root root password: root username: tux password: root Instructions: -Download and install 7zip (www.7-zip.org) -Extract files to HDD -Install included VirtualBox (not tested on other versions, but shouldn't matter) -Within VirtualBox make a new machine ----Machine/New --------Name: Savuka / Type: Linux / Version: Other Linux (32-bit) --------1024MB RAM -------- Use Existing virtual drive (point to extracted Savuka.vdi) ---- Machine/Settigns/Display: set video memory to 50 MB, enable 2D and 3D acceleration ---- Machine/Settings/Shared Folders: Create new machine folder. Point to any data directory, folder name: DATA, select Auto-mount. Note: "Folder name" must be 'DATA' in all caps to link on boot Thats it! More Info: www.osmanbilsel.net www.paulnobrega.net

A tool for autonomous and virtual topical data integration using the focused web-harvesting method.