Data Refining is a process that refines disparate data within a common context to increase the awareness and understanding of the data remove data variability and redundancy and develop an integrated data resource. Disparate data are the raw material and an integrated data resource is the final product. Data refining process may be composed of...

Data Refreshing is the process of updating active data replicates based on a regular known schedule. The frequency and timing of data refreshing must be established to match business needs and must be known by clients. Today companies operate in an information-centric and fast-paced world. As such data and information is very plentiful and readily...

Data Scrubbing is a technique to correct error by using a background task in order to periodically inspect the memory for errors.  The technique helps to  decode merge filter and even translate the source data so that the data for data warehouse remains valid. The error correction used is often the ECC memory or another copy of the...

Disparate Data are heterogeneous data. They are neither similar nor can be easily integrated with an organisations database management system. It differs in one or more aspects of an information system. Disparate data may be characterized by these basic problems 1. In an organization implementing a database system there is no one complete integrated...

Disparate Databases are heterogeneous databases In such database systems  are neither compatible electronically nor operationally. Technically speaking a database is repository of data that can provide for a centralized and homogeneous view of data to be used for multiple applications. The data in a database are not just randomly placed there...

Disparate Metadata Cycle is a kind of cyclic process in which disparate metadata gets  produced  rapidly.  With data warehouse implantations becoming more ubiquitous these days due to the fact that businesses can no longer function without being supplied by relevant data the use of metadata has become relevant too. As a short backgrounder...

Disparate Operational Data is generally used to support day-to-day business transactions.  They reflect current status of an organizations operational data. Dealing with disparate operational data is a very common everyday process in a data warehouse implementation. Since a data warehouse is built to contain the repository of current and historical...

In any database implementation it is always advised to normalize the database for optimal performance by reducing redundancy and maintaining data integrity. The process of normalization involves putting one fact in its appropriate place to make updates optimized at the expense of data retrievals. As opposed to having one fact in different places a...

The most general sense data quality is an indication of well the data is in terms of integrity and accuracy as it is stored in the data resource in order to meet the demand of business information. Other indicators of good quality data pertain to completeness timeliness and format though this may never apply anymore with today s advanced data cleansing...