Extract Transform Load Aggregate

Efficiently design, launch and monitor data processing in the data warehouse

ETLA

Extract Transform Load Aggregate (ETLA) is a dedicated proprietary solution that provides:

Effectively design a data warehouse model, metadata for ETL processes, and metadata for data quality management (DQM).

Automatic generation of data models and data processing in the data warehouse (DWH).

A data processing engine that provides standardized processes for data extraction, transformation, loading, data aggregation and data quality verification.

A unified environment for monitoring data processing in the data warehouse.

The ETLA toolkit allows you to efficiently design, launch and monitor data processing in a data warehouse.

ETLA (Design Environment) for designing the data warehouse model and defining data quality rules, and then automatically generating data models and processing processes;
The ETLA Runtime Environment (Runtime Environment) is a dedicated data processing engine that provides standardized processes for data extraction, transformation, loading, aggregation and data quality verification.
Tools for working in the ETLA (Client Environment), including a unified environment for monitoring data processing in the data warehouse.

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ETLA design environment

Designing a data warehouse model with data transformation rules.

The logical data model of the data warehouse is designed using the Logical Data Model [MS Excel] document template. The MS Excel document stores all the definitions of fact tables and dimension tables for the target data warehouse, along with descriptions of individual attributes (columns), data types, transformation rules and data loading.

Data Model Generator [T-SQL] is a dedicated routine that allows you to automatically populate the metadata of the biETLA runtime environment based on data designed at the Logical Data Model level.

Defining data quality rules

Data quality rules for data processing in the data warehouse are defined using the Data Quality Rules [MS Excel] document template. The MS Excel document collects the rules for each test, including the type of test, test parameters, test significance level and run parameters.

Data Quality Rules Generator [T-SQL] is a dedicated routine that allows you to automatically populate the metadata of the biETLA runtime environment based on data designed at the Data Quality Rules document level.

Expand ETLA's capabilities

By working optimally with DQM's data quality analysis tool, you can make the most of your company's valuable information resources and minimize the risk of inconsistencies and irregularities in your source data.

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