Data warehouse
A Data warehouse is a repository of integrated information, available for queries and analysis. Data and information are extracted from heterogeneous sources as they are generated. This makes it much easier and more efficient to run queries over data that originally came from different sources”. Another definition for data warehouse is : " A data warehouse is a logical collection of information gathered from many different operational databases used to create business intelligence that supports business analysis activities and decision-making tasks, primarily, a record of an enterprise's past transactional and operational information, stored in a database designed to favour efficient data analysis and reporting (especially OLAP)". Generally, data warehousing is not meant for current "live" data, although 'virtual' or 'point-to-point' data warehouses can access operational data. A 'real' data warehouse is generally preferred to a virtual DW because stored data has been validated and is set up to provide reliable results to common types of queries used in a business.

Business object
Business objects are objects in an object-oriented computer program that abstract the entities in the domain that the program is written to represent. For example, an order entry program needs to work with concepts such as orders, line items, and invoices and so on. A business object may represent each of these.

Business Objects are sometimes called Domain Objects (where the word Domain means the Business), and a Domain Model represents the set of domain objects and the relationships between them.

Good business objects will encapsulate all of the data and behavior associated with the entity that it represents. For example, an order object will have the sole responsibility for loading an order from a database, exposing or modifying any data associated with that order (i.e. order number, the order's customer account), and saving the order back to the database.

Business objects don't necessarily need to represent objects in an actual business (though they often do). They can represent any object related to the domain in which a developer is creating business logic for. The term is used to distinguish between the objects a developer is creating or using related to the domain and all the other types of object he or she may be working with such as user interface widgets and database objects such as tables or rows.

The concept of a business object is closely associated with the Component-based Scalable Logical Architecture (CSLA) developed by Rockford Lhotka

DataStage (IBM WebSphere DataStage) is an ETL (Extraction Transformation Loading) tool and part of the IBM WebSphere Information Integration suite. It uses a graphical notation to construct data integration solutions and is available in various different versions such as the Server edition and the Enterprise Edition.

It was formerly known as Ardent DataStage followed by Ascential DataStage and in 2005 was acquired by IBM and added to the WebSphere family.

DataStage Editions
Enterprise Edition: parallel jobs and server jobs. 
Server Edition: server jobs 
MVS Edition: mainframe jobs, developed on a Windows or Unix/Linux platform and transferred to the mainframe as compiled mainframe jobs. 
DataStage for PeopleSoft: a server edition with prebuilt PeopleSoft EPM jobs. 
DataStage TX: complex transactions, formerly known as Mercator. 
DataStage SOA: Real Time Integration pack can turn server or parallel jobs into SOA services

QualityStage is a data quality cleansing tool. 
ProfileStage is a data profiling tool. 
MetaStage is a metadata hub tool. 
DataStage TX is a tool for transforming complex transactions.