Efficient, real-time, low-code SaaS solution
The data lake real-time BI solution based on LakeSoul, the opensource lake warehouse framework, supports automatic real-time synchronization of various data sources such as databases, Kafka, and online logs; built-in multiple data modeling processes and index calculations, and the whole link is real-time Incremental update, real-time report update, quickly support business decisions.
Built-in multiple data source imports, multiple data modeling and index calculation links, eliminating the need for real-time calculations and ETL job development and deployment processes, one-click online real-time BI reports and AI models.
Real-time incremental update of the whole pipeline, support filtering, aggregation, join, deduplication and other data processing methods, with minute-level delay, and low computing overhead. Based on the data lake, massive data scale is supported at low cost.
Adapt to a variety of public and private clouds, can run on Hadoop, K8s clusters, rapid deployment; full interface configuration development, automatic job deployment and operation, simplify the development process, easy to get started.
One-stop solution from the data source to the BI applications
Web interface-based configuration of the entire process of data lake ingestion, modeling, and analysis, automatic real-time calculation of the entire pipeline, and real-time update of reports. Support real-time data warehouse modeling, BI analysis, AI model and other data applications to fully release the value of data
Solve the difficulties of real-time data warehouse and real-time analysis and calculation development, operation and maintenance, and realize efficient real-time and low-cost BI analysis application on the lake
BI/AI integrated computing and analysis, supports real-time data construction of multi-dimensional wide tables, machine learning sample concatenation and other scenarios, and seamlessly connects to multiple BI/AI engines.
Efficient and automatic
Without manual intervention, it can realize automatic synchronization of data sources, automatic incremental update of index calculation tasks, and automatic scheduling and operation of calculation jobs, reducing the burden on developers and reducing labor costs.
Cloud-native architecture, real-time data warehouse can be realized by using cheap object storage, elastic scaling of computing and storage, high efficiency and low cost.
Example of a real-time BI analytics solution for a data lake
Through simple configuration of data sources and business indicator calculations, real-time analysis on massive data lakes can be completed, and data such as real-time reports and real-time AI samples can be built quickly and easily
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