Product Benefits

Key Advantages

1. Powerful metric semantics: define any metric and drill down by any dimension

With a semantic data model and dynamic semantic functions, users can define complex metrics through configuration instead of writing SQL. The platform supports advanced metric logic, including window-style calculations, and enables drill-down analysis across business dimensions.

1. Standardized metric definition: eliminate ambiguity

Aloudata CAN breaks metrics into standardized metric elements. A small number of reusable elements can cover many derived metrics, reducing the cost of defining and managing metrics. The platform also checks for repeated or ambiguous definitions so metric logic stays consistent.

1. Define to develop: improve demand response speed

Based on Aloudata CAN's data virtualization engine, users define the business logic of a metric and the system automatically generates the calculation logic and pre-computation plan. This reduces metric development and operations work and can shorten response time from weeks to minutes.

1. Open metric services: define once, use everywhere

Aloudata CAN provides standardized APIs, JDBC access, and other integration interfaces. Metrics can be connected to internal applications, BI tools, and downstream data products so one definition can be reused across many scenarios.

1. Open architecture: decoupled from third-party engines

The platform uses a storage-compute separation architecture. Data does not need to be imported into the metric platform before it can be used, reducing data movement, storage cost, operations cost, quality risk, and latency. It can also reuse existing customer compute infrastructure and supports engine switching or upgrades.

Business Value

For Business Users

1. Higher analysis efficiency

Aloudata CAN hides complex ETL chains and technical table or field details. Business users can work with business-friendly metrics and dimensions, improving self-service analysis efficiency and reducing waiting time for new requirements.

1. Minute-level answers to metric questions

The semantic metric model supports roll-up, drill-down, filtering, and analysis across dimensions and time ranges. Teams can respond to management questions faster and with more consistent metric logic.

1. Better business insight

Metric attribution, monitoring, and alerting help business teams identify the reasons behind metric fluctuations and take action more quickly.

For IT Teams

1. Reduced data warehouse development and operations workload

IT teams no longer need to manually develop large volumes of SQL, testing scripts, release processes, and backfill jobs for every metric requirement. Metrics can be defined through configuration, reducing repetitive development and maintenance work.

1. Lower storage and compute cost

By reducing duplicate wide tables and summary tables, Aloudata CAN helps avoid repeated storage and computation. The application layer can be developed on demand through automated metric generation and acceleration.

1. Consistent metric quality

Aloudata CAN centralizes metric assets in one governed repository. It helps resolve metric silos, inconsistent definitions, difficulty finding trusted metrics, and high communication cost between IT and business teams.