Data integrity is a term used in databases. In its broadest use, "data integrity" refers to the accuracy and consistency of data stored in a database, data warehouse, data mart or other construct. The term - Data Integrity - can be used to describe a state, a process or a function - and is often used as a proxy for "data quality".
Data virtualization provides a virtual layer on top of all of your data storage systems so you can easily connect them even if they are in different data storage systems. With data virtualization, you can connect data across an organization in one central place without duplicating data into a data warehouse. no asnwers for that question, only what is that (that from that question) but can't search that sorry
mean does not mean the center of the data
what do you mean by data assembly?
The mean of a set of data is the sum of that data divided by the number of items of data.
it's data warehouse....data warehouse: it is a collection of multiple databases or it it is repository of data.data mining it is the process of extracting data from data warehouse.
Data warehouse is the database on which we apply data mining.
Data marts are combined into a data warehouse cannot be built alone without considering data marts. Both has equal importance to built proper data warehouse.
Metadata is data about data that provides information such as the structure, format, and characteristics of the data stored in a data warehouse. It is used in data warehouse architecture to facilitate data integration, data governance, and data lineage. Metadata helps users understand and manage the data in the data warehouse efficiently.
Data warehouse is a large repository of data. The data may or may not be of any use. Partitioning in Data warehouse can be done by forming clusters and then forming groups.Partitioning in datawarehouse can be done by forming clusters. Partitioning can be done on the basis of relation between the data.
Every data structure in the data warehouse contains the time element. Why?
One of the biggest benefits is that you can archive your data to a data warehouse. This can keep your main "production" database smaller which can provide some performance benefits. Also you can use the data warehouse to run complex queries and data-mining without adverse effects on the performance of your "production" application.
A data warehouse architecture is similar to various relational database systems. What makes the best architecture is the organization of the warehouse itself and the data it consist of.
Data warehouse is the pool of huge amount of data. The data in data ware house can be archived. And when the data is needed you can extract it from the archived files.
A distributed data warehouse is a type of data warehouse architecture where data is distributed across multiple servers or nodes in a network. This allows for improved scalability, performance, and fault tolerance compared to a centralized data warehouse. Distributed data warehouses can handle large volumes of data more efficiently by spreading the workload across multiple nodes.
A data warehouse stores structured data from various sources for analysis and reporting. It typically includes historical data, organized into tables, aimed at supporting decision-making processes. Data warehouses are optimized for complex queries and data aggregation.
catch important data from data warehouse.