Sliq
Sliq is an AI-powered data cleaning platform that transforms messy raw datasets into clean, analysis-ready data in minutes by automatically detecting and fixing common quality issues such as incorrect formats, missing values, schema inconsistencies, and formatting errors, so analysts and engineers spend less time on “janitor work” and more time on insights and modeling. It uses context-aware intelligence to understand the semantic domain of uploaded data (for example, whether it’s financial records, ecommerce logs, or medical data) and tailors a cleaning plan specifically for that dataset instead of applying one-size-fits-all rules. Users can upload files directly or integrate with workflows programmatically, and Sliq supports common data formats, including CSV, JSON, and Parquet, while seamlessly integrating into existing data ecosystems.
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Querri
Querri is an AI-powered data analytics platform designed to make data collaboration effortless by enabling users to connect, clean, analyze, and visualize data all in one place. It features a natural-language interface that lets you ask questions in plain English and instantly get visual answers. It also includes automated data cleansing and ingestion tools that handle messy or disparate files (CSV, Excel, JSON, Parquet) and cloud-storage sources (Google Drive, OneDrive, Dropbox), joining and reformatting them so you can start analyzing without delay. A drag-and-drop dashboard builder enables the quick creation of shareable reports, while built-in integrations cover spreadsheets and business apps (Excel, Smartsheet, QuickBooks, Airtable, among others). Querri offers white-label capabilities so you can embed or brand the analytics engine within your own product.
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CSViewer
CSViewer is a fast and free Windows desktop application for viewing and analyzing large delimited text and binary data files, such as CSV, TSV, Parquet, and QVD. It can load millions of rows in seconds and offers advanced filtering, instant profiling with aggregates, null counts, and outlier detection. Users can export filtered data, save analysis views, and visualize data through charts and cross-tables. CSViewer is designed for easy exploratory analysis without sending data to the cloud. Aggregates and charts are updated immediately when a filter is applied or changed. Null counts, uniques, min/max values, aggregates, etc. for every column. Export the filtered subset of rows into another file for sharing or use in another application. Convert data from one file format to another, e.g. from CSV to QVD. When you export into the native for CSViewer .dset file format, data is saved together with filters and charts for your convenience.
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Tenzir
Tenzir is a data pipeline engine specifically designed for security teams, facilitating the collection, transformation, enrichment, and routing of security data throughout its lifecycle. It enables users to seamlessly gather data from various sources, parse unstructured data into structured formats, and transform it as needed. It optimizes data volume, reduces costs, and supports mapping to standardized schemas like OCSF, ASIM, and ECS. Tenzir ensures compliance through data anonymization features and enriches data by adding context from threats, assets, and vulnerabilities. It supports real-time detection and stores data efficiently in Parquet format within object storage systems. Users can rapidly search and materialize necessary data and reactivate at-rest data back into motion. Tension is built for flexibility, allowing deployment as code and integration into existing workflows, ultimately aiming to reduce SIEM costs and provide full control.
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