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- PROC SQL: Beyond the Basics Using SAS, Kirk Paul Lafler
- PROC SQL (3rd ed.) by Kirk Paul Lafler (ebook)
- Sas best informat
- About This Item
It involves planning, modeling, creating, monitoring, and adjusting to satisfy the endless assortment of user requirements without impeding resource requirements. Of central importance to database design is the process of planning. Planning is a valuable component that, when absent, causes a database to fall prey to a host of problems including poor performance and difficulty in operation. Database design consists of three distinct phases, as illustrated in Figure 1. A physical file consists of one or more records ordered sequentially or some other way. These languages were generally designed and used to mimic the way people process paper forms.
Multisets have no order, and members of a multiset are of the same type using a data structure known as a table. For classification purposes, a table is a base table consisting of zero or more rows and one or more columns, or a table is a virtual table called a view , which can be used the same way that a table can be used see Chapter 8, Working with Views. Redundant Information One of the rules of good database design requires that data not be redundant or duplicated in the same database.
PROC SQL: Beyond the Basics Using SAS, Kirk Paul Lafler
The rationale for this conclusion originates from the belief that if data appears more than once in a database, then there is reason to believe that one of the pieces of data is likely to be in error. Furthermore, redundancy often leads to the following: Inconsistencies, because errors are more likely to result when facts are repeated. Update anomalies where the insertion, modification, or deletion of data may result in inconsistencies. Another thing to watch for is the appearance of too many columns containing NULL values.
When this occurs, the database is probably not designed properly. To alleviate potential table design. When properly done, this ensures the complete absence of redundant information in a table. Normalization The development of an optimal database design is an important element in the life cycle of a database. Not only is it critical for achieving maximum performance and flexibility while working with tables and data, it is essential to the organization of data by reducing or minimizing redundancy in one or more database tables.
The process of table design is frequently referred to by database developers and administrators as normalization. The normalization process is used for reducing redundancy in a database by converting complex data structures into simple data structures. It is carried out for the following reasons: To organize the data to save space and to eliminate any duplication or repetition of data. To enable simple retrieval of data to satisfy query and report requests. To simplify data manipulation requests such as data insertions, updates, and deletions. To reduce the impact associated with reorganizing or restructuring data as new application requirements arise.
The normalization process attempts to simplify the relationship between columns in a database by splitting larger multicolumn tables into two or more smaller tables containing fewer columns. The rationale for doing this is contained in a set of data design guidelines called normal forms. The guidelines provide designers with a set of rules for converting one or two large database tables containing numerous columns into a normalized database consisting of multiple tables and only those columns that should be included in each table.
The normalization process consists of multiple steps with each succeeding step subscribing to the rules of the previous steps.
PROC SQL (3rd ed.) by Kirk Paul Lafler (ebook)
Normalization helps to ensure that a database does not contain redundant information in two or more of its tables. In an application, normalization prevents the destruction of data or the creation of incorrect data in a database. What this means is that information of fact is represented only once in a database, and any possibility of it appearing more than once is not, or should not be, allowed. As database designers and analysts proceed through the normalization process, many are not satisfied unless a database design is carried out to at least third normal form 3NF.
While the normalization guidelines are extremely useful, some database purists actually go to great lengths to remove any and all table redundancies even at the expense of performance. This is in direct contrast to other database experts who follow the guidelines less rigidly in an attempt to improve the performance of a database by only going as far as third normal form or 3NF. Whatever your preference, you should keep this thought in mind as you normalize database tables. A fully normalized database often requires a greater number of joins and can adversely affect the.
Celko mentions that the process of joining multiple tables in a fully normalized database is costly, specifically affecting processing time and computer resources. Normalization Strategies After transforming entities and attributes from the conceptual design into a logical design, the tables and columns are created. This is when a process known as normalization occurs. Normalization refers to the process of making your database tables subscribe to certain rules. Many, if not most, database designers are satisfied when third normal form 3NF is achieved and, for the objectives of this book, I will stop at 3NF, too.
To help explain the various normalization steps, an example scenario follows.
A table is considered to be in first normal form when all of its columns describe the table completely and when each column in a row has only one value. A table satisfies 1NF when each column in a row has a single value and no repeating group information. Essentially, every table meets 1NF as long as an array, list, or other structure has not been defined. The following table illustrates a table satisfying the 1NF rule because it has only one value at each row-and-column intersection. Table 1. A table is said to be in second normal form when all the requirements of 1NF are met and a foreign key is used to link any data in one table which has relevance to another table.
The very nature of leaving a table in first normal form 1NF may present problems due to the repetition of some information in the table. One noticeable problem is that Table 1. Another problem is that there are misspellings in the customer name.
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Although repeating information may be permissible with hierarchical file structures and other legacy type file structures, it does pose a potential data consistency problem as it relates to relational data. To describe how data consistency problems can occur, let s say that a customer takes a new job and moves to a new city. In changing the customer s city to the new location, it would be very easy to miss one or more occurrences of the customer s city resulting in a customer residing incorrectly in.
Assuming that our table is only meant to track one unique customer per city, this would definitely be a data consistency problem. Essentially, second normal form 2NF is important because it says that every non-key column must depend on the entire primary key. Tables that subscribe to 2NF prevent the need to make changes in more than one place. What this means in normalization terms is that tables in 2NF have no partial key dependencies.
As a result, our database that consists of a single table that satisfies 1NF will need to be split into two separate tables in order to subscribe to the 2NF rule. The tables in 2NF would be constructed as follows. Consequently, tables are considered to be in third normal form 3NF when each column is dependent on the key, the whole key, and nothing but the key.
But, it is not uncommon for others to normalize their database tables to fourth normal form 4NF where independent one-to-many relationships between primary key and non-key columns are forbidden. Some database purists will even normalize to fifth normal form 5NF where tables are split into the smallest pieces of information in an attempt to eliminate any and all table redundancies.
Although constructing tables in 5NF may provide the greatest level of database integrity, it is neither practical nor desired by most database practitioners. There is no absolute right or wrong reason for database designers to normalize beyond 3NF as long as they have considered all the performance issues that may arise by doing so.http://dktrainingconsultancy.co.uk/scripts/2019-12-23/qerus-poemas-para-mujeres.php
Sas best informat
A common problem that occurs when database tables are normalized beyond 3NF is that a large number of small tables are generated. In these cases, an increase in time and computer resources frequently occurs because small tables must first be joined before a query, report, or statistic can be produced. As was stated earlier, although PROC SQL s naming conventions are not as rigid as other vendor s implementations, care should still be exercised, in particular when PROC SQL code is transferred to other database environments expecting it to run error free.
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- PROC SQL: Beyond the Basics Using SAS, Third Edition.
- PROC SQL: Beyond the Basics Using SAS, Third Edition.
- PROC SQL: Beyond the Basics Using SAS, Second Edition.
- Collins Junior Illustrated English Dictionary (2nd Edition).
If a column name in an existing table conflicts with a reserved word, you have three options at your disposal: 1. Physically rename the column name in the table, as well as any references to the column. Data integrity is a critical element that every organization must promote and strive for. It is imperative that the data tables in a database environment be reliable, free of errors, and sound in every conceivable way.
The existence of data errors, missing information, broken links, and other related problems in one or more tables can impact decisionmaking and information reporting activities resulting in a loss of confidence among users. These rules consist of table and column constraints, and will be discussed in detail in Chapter 5, Creating, Populating, and Deleting Tables.
Referential Integrity Referential integrity refers to the way in which database tables handle update and delete requests. Database tables frequently have a primary key where one or more columns have a unique value by which rows in a table can be identified and selected.
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Other tables may have one or more columns called a foreign key that are used to connect to some other table through its value. Database designers frequently apply rules to database tables to control what happens when a primary key value changes and its effect on one or more foreign key values in other tables. These referential integrity rules apply restrictions on the data that may be updated or deleted in tables. Referential integrity ensures that rows in one table have corresponding rows in another table. This prevents lost linkages between data elements in one table and those of another enabling the integrity of data to always be maintained.