Palo for Data Integration (ETL Server)
Extraction, Transformation and Loading of Mass Data from Heterogeneous Sources
- Execute data imports in a quick, easy and flexible manner, fully automated and web-based
- Interface to all common relational databases and SAP ERP (Enterprise Resource Planning) and BW (Business Warehouse) systems
- Drill-through from consolidated Palo OLAP-data down to the last detail of the source data
- A complete web-based solution for optimal integration
Data Integration for Palo Models
Unlike other ETL tools, the Palo ETL Server has been tailored to meet the particular requirements of Palo. Palo OLAP Server is supported as both the source and the target system in an efficient manner. The handling of cubes and dimensions is straightforward with flexibility in generating frequently used time hierarchies. The tool makes the conversion from a relational model to an OLAP model simple and efficient.
The ETL Process in 3 Steps:
Extracts:
Retrieval of data from source systems is defined in “Extracts”. All common relational database systems such as MySQL, Microsoft SQL Server and Oracle can be connected via JDBC interface. Besides access to the Palo OLAP Server, data can be extracted from flat files, XML files, Web services and LDAP systems. A direct link to SAP systems via RFC/BAPI is facilitated through Palo SAP Connectivity.
Transforms:
The relevant transformation steps are defined in „Transforms“: Normalization, aggregation, join, filter and sort as well as particular hierarchical operations of dimension data. For field by field transformations, predefined functions are available, e.g. mapping and concatenation. Additional custom transformations can be implemented with a scripting language or Java. The result of Transforms as well as for Extracts can already be verified during the modeling phase using the data preview.
Loads:
With Loads, data is written into the target system. The creation of dimensions and cubes in the Palo OLAP Server is achieved in a highly performant manner through optimal utilization of the interface. In addition, data can be written back into relational database systems and flat files. Jobs group multiple Loads and by using variables they can be made dynamic. They are therefore the basis for a time-controlled and fully automated loading process.
Drill-Through:
Drill-Through describes the linking from one data source to another, most often a more detailed data source. With the help of Palo ETL, the Drill-Through to the document data in the source systems is made possible by caching the required data. With this, information on the origin of the data can be displayed on a high level of detail via navigation.
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