What is Data Stage

Datastage is used in a large organization as an interface between different systems. It takes care of extraction, translation, and loading of data from source to the target destination. It was first launched by VMark in mid-90’s. With IBM acquiring DataStage in 2005, it was renamed to IBM WebSphere DataStage and later to IBM InfoSphere.

Various version of Datastage available in the market so far was Enterprise Edition (PX), Server Edition, MVS Edition, DataStage for PeopleSoft and so on. The latest edition is IBM InfoSphere DataStage

Data Stage Solutions for Business

IBM WebSphere DataStage is of the industry leading Extract, Transform, Lead (ETL) tools in the market used to transfer the data from old legacy systems to the new DW systems. DataStage offers the most powerful ETL solution.

IBM® WebSphere® DataStage® provides the capability to perform extract, transform, and load (ETL) operations from multiple sources to multiple targets, including Db2® for z/OS®.

This ETL solution supports the collection, integration, and transformation of large volumes of data, with data structures ranging from simple to highly complex. WebSphere DataStage manages data that arrives in real time and data received on a periodic or scheduled basis.

ETL operations with WebSphere DataStage are log-based and support a broad data integration framework. You can perform more complex transformations and data cleansing, and you can merge data from other enterprise application software brands, including SAP, Siebel, and Oracle.

IBM Info Sphere Data Stage

IBM Info Sphere Data Stage is a powerful data integration tool. It integrates data across multiple systems using a high performance parallel framework, and supports extended metadata management and enterprise connectivity. The scalable platform provides more flexible integration of all types of data, including big data at rest (Hadoop-based) or in motion (stream-based), on distributed and mainframe platforms.

IBM® InfoSphere® DataStage® is a leading ETL platform that integrates data across multiple enterprise systems. It leverages a high performance parallel framework, available on-premises or in the cloud. The scalable platform provides extended metadata management and enterprise connectivity. It integrates heterogeneous data, including big data at rest (Hadoop-based) or big data in motion (stream-based), on both distributed and mainframe platforms. It supports IBM Db2 Z and Db2 for z/OS, applies workload and business rules, and integrates real-time data in an easy to deploy platform.