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.
Typical relational databases are designed for on-line transactional processing (OLTP) and do not meet the requirements for effective on-line analytical processing (OLAP). As a result, data warehouses are designed differently than traditional relational databases.
Datawarehosing is a process of creating,queriring and populating datawarehouse. it includes a number of discrete technologies like Identifying sources Process of ECCD, ETL which includes data cleansing , data transforming and data loading to targets.
A Data warehouse is a subject oriented, integrated, time-variant, nonvolatile collection of data to enable decision making across disparate group of users.
A data warehouse is a repository containing subject-oriented, integrated,time-variant and non-volatile collection of data, used for companys decision support systems requirement
Datawarehousing is a subject oriented, authoritative,integrated historical database reflective of changes over meaningful time periods in order to facilitate query and analysis for useful management decision making.
Datawarehousing is a subject oriented, authoritative,integrated historical database reflective of changes over meaningful time periods in order to facilitate query and analysis for useful management decision making.
Datawarehouse contains a collection of historic(history of data) ,integrated ,non-volatile data ,which is used for analysing and developing forecasting reports.
Data-Warehouse-Prozess (englisch data warehousing) ist der Prozess zur Bewirtschaftung und Auswertung eines Data-Warehouses, der die folgenden Schritte umfasst: #Datenbeschaffung: das heißt die Extraktion der relevanten Daten aus den Quellsystemen, Transformation und gegebenenfalls Bereinigung der Daten (Data Cleansing) in einem Arbeitsbereich (englisch staging area) sowie Laden in das Data-Warehouse. Dieser Schritt wird auch Extract-Transform-Load-Prozess (ETL-Prozess) genannt.
