From data to modeling services

Committed to mining value from massive datasets, quickly building prediction models from raw data, targeting key customers, incorporating deep systems, and serving data analysts and scientists.
It provides a one-stop toolkit for efficient data collection, data cleansing, data analysis, and data modeling to improve data connectivity exploration, and modeling efficiency in order to quickly deal with business changes.

How do you quickly access data?
Connected to a variety of data storage systems, it can automatically identify multiple data formats, immediately access massive datasets, and improve the efficiency of data analysis.
How can data exploration help us work together more efficiently?
With a wealth of preset operations, individuals in different roles can use their own skills to quickly process the data in an exclusive exploration environment that fosters efficient collaboration within data science teams.
How to improve the development of models?
A unified data development environment, a variety of machine learning extended algorithm packages and training frameworks, evaluations of multiple model tuning main indicators, and unified management for multiple versions of the model all contribute to improved model development.
Multiple data source connections
Automatically detect dataset formats and architectures; read and observe datasets from a variety of data storage systems; with instant access to data, there is no need to write strict formatting before reading a dataset.

Visualization of data analysis
Data at each step can be analyzed more intuitively by looking at data distribution, data quality, and many other aspects explore and plot data interactively using more than 20 charts easily access multiple built-in visual processors for codeless data analysis.

Provides you with:

Efficient collaboration for data exploration

A rich set of preset operators (Join/Group By/Distinct, etc.) allows data scientists to conduct ad hoc exploration of datasets in a quick and efficient way support for multiple languages (Python/Scala/SQL, etc.) meets the needs of data scientists seeking more complex and customized dataset exploration.

Machine learning model evaluation
Efficient connection of massive datasets; quick loading of multiple data file formats and large-scale data sources; preprocessing without the need for code. A unified data development environment that supports multiple machine learning extension algorithm packages and training frameworks while integrating mainstream open source AI platforms. Possessing independent resource exploration projects, team members can collaborate on the same project and shorten the model development cycle.Support for main indicator evaluation, model tuning, and unified management of multiple versions.

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