Data Warehousing helps in rapid retrieval of stable data. Most of the data stored in a Data Warehouse is of historical nature. The existing data in a Data Warehouse is never modified, and is refreshed by adding data from the database associated with the TPS. The following activities are performed for creating a Data Warehouse [...]
Continue reading → A Data Warehouse is a repository database that efficiently extracts data from existing systems for the rapid analysis and reporting of information in a business enterprise. Operations, such as querying and report generation can be performed on the data stored in Data Warehouse. These qeries may be analytical, ad hoc, or statistical in nature. Various [...]
Continue reading → Business success is determined by the ability to take timely and accurate decisions. The accuracy of these decisions, in turn, is dependent on the information that is made available to the decision makers. With the wide variety of data being generated by the business, the problems that emerge include converting different formats into one common [...]
Continue reading → If checks are not applied while defining and creating tables, the data stored in the tables can become redundant. For example, if you do not store the data about all the employees with complete address details, then the data would not be useful. Similarly, if a database used by the Human Resources department stores employee [...]
Continue reading → The normalization theory is based on the fundamental notion of fundamental dependency. First, let’s examine the concept of functional dependency. Given a relation R, attribute A is functionally dependent on attribute B if each value of A in R is associated with precisely one value of B. In other words, attribute A is functionally dependent [...]
Continue reading → A table is said to be in the 1 NF when each cell of the table contains precisely one valid. Consider the following table PROJECT. PROJECT The data in the table is not normalized because the cells in PRJCODE and HOURS have more than one value. By applying the 1NF definition to the PROJECT table, [...]
Continue reading → Normalization is scientific method of breaking down complex table structures into simple table structures by using certain rules. Using this method, you can, reduce redundancy in a table and eliminate the problems of inconsistency and disk space usage. You can also ensure that there is no lose of information. Normalization has several benefits. It enables [...]
Continue reading → An RDBMS uses associative addressing; that is, it identifies and locates rows by value. The physical address is transparent to the user. Therefore, relational systems require keys that can uniquely identify the rows of a table. There are various types of keys, some of which we are already familiar with. These are Primary Foreign Candidate [...]
Continue reading → The conceptual model reflects entities and their relationships based on the data processing needs of an organization. To develop a database that satisfies the information needs of the present as well as the future, you must design a conceptual model of the database first. The conceptual model design is not concerned with the implementation and operation [...]
Continue reading → INTERSECT: The Intersect operator builds a relation consisting of tuples that appear in both relations. Consider tables A and B. Nancy is doing a double major; therefore, her name appears in both tables. An intersect operation on tables A and B extracts the row common to both relations. The INTERSECT operations works on union compatible [...]
Continue reading → The relational model is based on the principle of relational algebra. Relational algebra is a collection of operators that operate on relations. Each operator takes one or two relations as its input and produces a new relation as its output. RESTRICT: The Restrict operator extracts specified tuples or rows from a given relation, based on [...]
Continue reading → One major difference between the relational model and earlier data models is that explicit pointers such as parent -child relationships of the hierarchical model are banned from the relational model. Yet , relationships do exist in the relational model. However, these relationships are represented by common data values stored in two or more tables. All [...]
Continue reading → The organizing principle in a relational database is the table, a tabular arrangement of data values. Each table in a database has unique table name that identifies its contents. A table is called a relation. The row [or record] in the table is called a tuple and the column [ or field ] is called [...]
Continue reading → We are familiar with the ER model, which is an example of an object based logical model. There are other data models one of those is Record based logical model. Record based model consists of three types. The three types of record based models are : Hierarchial model Network model Relational model In a Hierarchical [...]
Continue reading → Often, several operations on the database form a single logical unit of work. An example is a funds transfer, in which one account (say A) is debited and another account (say B) is credited. Clearly, it is essential that either both the credit and debit occur, or that neither occur. That is, the funds transfer [...]
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