One stop, modular management

From data mining and development to data analysis, application and operation, Kepler provides one-stop, modular full lifecycle management. Through low code and no code visualization operations, the analysis results are saved in stages. Kepler enables users to focus on understanding business, efficiently complete data processing, and form a stable operation mechanism.

Access to all categories of data assets

Kepler supports the definition and relationship of four types of data application assets: labels, indicators, reports, and models. It realizes the sharing of different types of data assets, further improves the value of data, and avoids data duplication and data ambiguity.

Data asset operation management

Kepler views data assets such as indicators and labels from an original operational perspective. By analyzing the popularity of indicator labels, the use preference of each business department, the statistics of common indicators, intelligent recommendation of indicators, feedback of indicator effects, indicator contribution and other intelligent operation functions, the enterprise data assets can continue to generate value.

Industry knowledge precipitation and practice

Different from traditional BI tools, even number technology has built Kepler‘s summary model design, indicator label classification system, indicator label information summary, and Story analysis report template based on rich project experience and knowledge accumulation in the past, which really breaks through the barriers between technology and business departments.

Support high-performance computing engine

Kepler relies on OushuDB computing storage engine to greatly improve the efficiency of massive data analysis. By introducing stream computing, Kepler realizes the combination of static tables and stream computing in the data analysis process, more completely depicts the analysis object, and greatly improves the analysis accuracy.

Widely applicable to various scenarios

Kepler is widely applicable to online data filling, management of cockpit and large screen, automation of approval process, data portal, index asset directory, external sharing of data assets, data exploration and analysis, and building of data mart to meet the needs of data analysis and application in different scenarios.