Use of Boolean Tools in Searching a Database - Research Paper Example

? Databases: Creating Information from Data Describe a Database A database is fundamentally described as the collection of valuable information that is organized in such a way so that a particular computer based program can quickly select desired portions of data. In precise, a database is also typically defined as an alphabetical arrangement of names that deliver precious information in a grouping of dissimilar formats. It is worth mentioning that a database can also be viewed as a form of electronic filing system. Various examples of database might include a telephone book, address book and Census Bureau Data among others. After acquiring a brief idea about the notion of a database, certain facets of a database can be apparently observed. In this regard, the facets comprise advanced as well as basic searching options, text box, online help, and a search history along with a ‘results’ display’. Moreover, with regard to determining the characteristics of a database, it can be viewed that a database possesses the capability of printing, saving as well as e-mailing the desired results along with the ability to choose or mark precious records. There are certain advantages as well as disadvantages of a database. In this similar concern, the advantages of a database include the availability of effectively shared data, greater centralized control, enhanced data integrity, flexible conceptual design along with improved database systems as well as data security. On the other hand, the disadvantages of a database encompass the requirement for numerous external bases, higher acquisition along with operational costs, greater reliance upon the operations based on Database Management System and time consuming nature especially for individual applications (University of Queensland, 2009). It has been apparently observed that a particular research database related to any nursing field such as congenital cardiac disease is normally suited to conduct in-depth investigations of functional outcomes (Hickey, McCrindle, Caldarone, Williams & Blackstone, 2008). Specially mentioning, the formation as well as the maintenance of an effective database system can provide to be quite beneficial for enhancing the provided care to the patients by a considerable level. It can be affirmed in this similar context that the formulation of a well-structured database would enhance patients’ care through holding detailed health related information about the patients, accessing and readily updating them in an effective manner. It can be apparently observed that maintaining databases has brought about a plethora of improvements regarding patient care by maintaining medical records of the patients in a comprehensive manner, assessing the quality and the outcome of care at large. It can be stated that maintaining databases can facilitate to enhance patients’ care through several ways. These ways comprise providing necessary details about illnesses of the patients to the medical practitioners, constructing safety alerts and producing a comprehensive disease summary along with treatment among others. The greatest advantage of formulating a database within the circumstance of enhancing patients’ care can be recognized as the instant accessibility of all indispensable information when treating a complex patient enabling the respective healthcare department to deliver effective care to that specific complex patient. In this present globalization driven era, hospitals and various healthcare institutions are often viewed to be maintaining as well as sharing medical records and health related information about the patients by a greater level. This can be owing to the reason of accomplishing their respective interoperability and efficiency objectives (Russel, 2013). Thus, it can be affirmed that databases are broadly used by different healthcare institutions in order to enhance patients care at large. 2. Use Of Boolean Tools In Searching A Database Boolean tools can be duly considered as a collection of effective logical systems that have been normally designed for producing better search results through formulating precise queries. In general terms, these tools are often regarded as an efficient system which enables a searcher to match a database based on specific relationships between the keywords at the time of searching. It can be apparently viewed that Boolean tools are often used in various search engines and periodical databases for the purpose of retrieving significant items automatically. It is worth mentioning in this similar concern that Boolean tools are also used in searching a particular database by a considerable level. The different Boolean tools that are used in searching a database comprise ‘AND’, ‘OR’ and ‘NOT’. These tools are often regarded as Boolean logical operators that are broadly used in this high-tech era for the purpose of retrieving items effectively from different search engines and also for producing better search results. In this regard, the tool or the logical operator of ‘AND’ acts as a limiter as it tends to limit the quantity of responses by denoting that multiple search items are present in the retrieved document. In relation to search a database, this particular Boolean tool is normally used to signify database that multiple search items are required to be retrieved. Moreover, this tool is executed for the purpose of connecting distinct concepts or terms. It can be stated that one of the effects of ‘AND’ tool is to restrict or narrow the figure of documents that have been retrieved by the users. The usage of this tool in searching a database can be better understood with the help of the following pictorial illustration. Source: (University of Maryland, 2013; Sewell & Thede, 2013). The Boolean tool or the logical connector of ‘OR’ is mainly used in searching a website for the purpose of communicating to the database that the users desire to retrieve valuable documents that entail one or numerous specified terms or concepts. With regard to determining the use of ‘OR’ tool in searching a website, it has been viewed that this particular tool or logical connector is generally executed with the intention of connecting related terms or concepts. In this regard, this tool is often regarded as one of the powerful tools especially in the context of keyword searching. The effectiveness of ‘OR’ tool or logical connector in searching a database lies in the fact that numerous dissimilar terms can be adopted as well as executed in order to express a specific concept. One of the crucial effects of this tool can be recognized as raising or expanding the quantity of retrieved documents performed by various users. A diagrammatical representation has been provided below for better comprehension about ‘OR’ Boolean tool. Source: (University of Maryland, 2013; Sewell & Thede, 2013). On the other hand, the Boolean tool or the logical connector of ‘NOT’ limits the figure of responses of the retrieved documents and also tends to eliminate substantial bad or false results that arise from the consequences of web search tools. In other words, it can be affirmed from a broader outlook that this particular tool or logical connector is mainly executed for communicating to the database that it does not require retrieving any document or concept. This particular tool can be better understood with the aid of the following pictorial illustration. Source: (University of Maryland, 2013; Sewell & Thede, 2013). 3. Role of Databases In Improving Patient Care In order to determine the role of databases in improving the care of the patients, it can be affirmed that the hospitals together with their respective health systems belonging to this present day context are sharing more information about the patients as compared to preceding years through forming databases. It has been apparently observed that the modern clinicians nowadays, store along with share different sorts of information concerning nursing notes, financial data, medication and supply inventory among others through constructing effective databases. The major reason for the modern clinicians and the hospitals along with their health systems to formulate efficient databases can be to attain their respective efficiency and interoperability goals by a considerable level. One of the major roles performed by databases is saving the time of clinicians that they expend on repetitive data entry. This particular role facilitates to enhance the workflow efficiency which in turn ultimately leads to greater improvement in patient care. In addition, the other imperative role played by databases within the circumstance of enhancing patient care can be apparently observed as centralizing as well as updating valuable information of the patients such as treatment and medication. The aspect concerning superior clinician workflow management can be duly considered as one of the decisive roles played by databases in the context of delivering effective care to the patients. In this regard, it can be affirmed that the time of clinicians is not effectively utilized at the time when related databases are not shared efficiently between various hospital departments. Moreover, due to non-sharing of databases, several information relating to the patients such as admission, hospital pharmacy, activities involved in operating room and follow-up appointments among others have to be reentered several times that can certainly hamper the management of clinical workflow at large. This particular complexity or problem can be solved by forming effectual databases through storing the above discussed information in a single place, facilitating the users to access the valuable information whenever required and most vitally eliminating the repeated data entry (Russel, 2013). It is worth mentioning that apart from making better management in clinical workflow, databases also play an indispensable role in enhancing the security of patients and care coordination. Through databases, the care provided to patients generally gets improved by ensuring valuable information to be available across manifold departments of the healthcare institutions. Besides, databases also aid in improving patient care through upgrading face-to-face experience of the patients by a considerable level. This face-to-face experience of the patients can be associated with various significant aspects such as medication along with its supply usage and caregiver information among others (Russel, 2013). Another valuable role played by databases in the context of improving patient care can be apparently viewed to be ascertaining greater access towards valuable information of the patients. This can be justified with reference to the fact that today’s modern healthcare is regarded as a complex as well as a dynamic environment wherein there lays the presence of numerous physicians, lab technicians and therapists among others. Thus, effective management of retrieving valuable patient related data can be performed by formulating databases by a greater extent. It has been viewed that the formulation of effective databases can enhance care coordination and most significantly patient care at large through performing certain imperative functions. These functions encompass bearing comprehensive, accessible as well as updateable patient related information, periodically assessing quality along with outcome of care and facilitating easy accessibility of aggregate data for conducting research regarding the improvement of patient care (Oracle, 2011). Thus, on the basis of the above discussion, it can be affirmed that databases play a decisive role in enhancing patient care by a significant level. 4. Methods of Discovering Knowledge In Both Relational And Large Databases Prior to identifying the methods of discovering knowledge in both relational and large databases, it is quite essential to comprehend the inner meaning of knowledge discovery in databases (KDD). KDD is fundamentally described as an exploratory as well as an automatic study along with modeling of huge data repositories. It is often duly considered as a sort of organized procedure which recognizes novel, useful, understandable and valid patterns from huge and composite data sets. The following graphical representation depicts the methods of discovering knowledge in both relational and large databases. Source: (Maimon & Rokach, n.d.). On the basis of the above pictorial illustration, it can be affirmed that there are several methods of discovering knowledge in both relational and large databases. In this regard, the methods have been described in the following discussion. Domain Understanding and KDD Goals This particular method builds a setting for comprehending what should be done by adopting as well as executing effective decisions. Moreover, the method defines the objectives of the end users and most vitally enables them to learn about the setting wherein the procedure of knowledge discovery would occur. Selection & Addition After the determination of the KKD goals, this method identifies what sorts of data are accessible, along with acquiring extra necessary data and integrating all data into one specific data set for effective knowledge discovery. This method is quite important to discover knowledge in both relational and large databases owing to the reason that the procedure concerning knowledge development largely relies upon selected necessary data by a certain degree (Maimon & Rokach, n.d.). Preprocessing and Data Cleaning Through this particular method, the aspect of data reliability is largely enhanced by a considerable level through preprocessing the relevant and the valuable information. This method comprises the notion of data cleaning in the form of handling any sort of missing value and removing noises (Maimon & Rokach, n.d.). Data Transformation This method helps in discovering knowledge in both relational as well as large databases through generating better data for effective preparation as well as development of data mining. It is regarded as one of the significant aspects related to discovering knowledge owing to the reason that this method is quite project-specific (Maimon & Rokach, n.d.). Data Mining The method of data mining also plays a decisive role in discovering knowledge in both relational and large databases through making appropriate decisions concerning which sorts of data mining tool would be used in the aforesaid process (Maimon & Rokach, n.d.). Selecting the Algorithm of Data Mining This particular method tends to select specific methods with the objective of comprehending the conditions under which an algorithm of data mining is most apt (Maimon & Rokach, n.d.). Employing the Algorithm of Data Mining This specific method helps in discovering knowledge in both relational as well as large databases through adopting and executing the selected algorithm numerous times until a desired result is obtained (Maimon & Rokach, n.d.). Evaluation and Interpretation It is worth mentioning that this particular method interprets and evaluates the rules as well as the patterns with respect to the KKD goals identified above. In this particular method, greater emphasis is laid upon determining the comprehensibility and the usefulness of the objectives associated with KKD (Maimon & Rokach, n.d.). Visualization and Integration of Discovered Knowledge This particular method represents incorporation of knowledge into another system for making further actions relating to the discovery of knowledge in both relational and large databases. The method concerning the visualization as well as the incorporation of discovered knowledge largely determines the efficacy of the entire KKD procedure by a considerable level (Maimon & Rokach, n.d.). 5. Differentiate Methods of Viewing Data in A Database Prior to identifying and differentiating the methods of viewing data in a particular database, it is quite indispensable to acquire a brief idea about different levels of data that need to be viewed. In this regard, the various data labels comprise schema, physical and subschema. Schema represents overall logical outlook or view of the interrelations amid data in a specific database. On the other hand, subschema denotes a logical outlook of data affiliation required to develop the application programs of the specific end users. Finally, physical data level signifies identification about how data is physically stored, arranged as well as accessed in various devices of a particular computer system. After acquiring a brief understanding about various data levels, numerous methods can be apparently viewed to be largely accessible for viewing diverse sorts of data in a particular database. In this similar concern, the various methods of viewing data in a database comprise Structured Query Languages (SQL), data modeling or logical design, normalization and physical design. It is strongly believed that with the aforesaid methods, the users can view data in a database by a significant level (UMSL, n.d.). A detailed analysis and differentiation of these methods have been discussed in the following section: SQL is regarded as an international standard based access language which is typically used particularly for defining as well as manipulating data in databases. The notion of data modeling or logical design denotes recognizing the entity classes that are represented in a particular database along with forming effective interrelations between the pairs of these entities. The term ‘normalization’ is often regarded as the generalization of the logical outlook of data in relational along with huge databases. The aspect of logical design represents answering the queries that rise by typical databases. In order to differentiate the methods of viewing data in a database, it can be stated that there exist a vital demarcation between SQL and data modeling or logical design. In this regard, the demarcation lies in reference to the fact that SQL is broadly used in maintaining huge databases, whereas data modeling or logical design is applied in relational databases. One of the main disparities between normalization and physical design is that the former simplifies the logical representation of data in both relational and large databases and the latter tends to answer the queries of the databases (UMSL, n.d.). 6. Steps in Creating a Database There are two separate steps in creating a database. One of the steps in forming a database includes the following: 1. Creation of the database 2. Defining the views as well as the fields in the database 3. Setting strong permissions in the database and, 4. Creating database reports (optional). The other steps in creating a database encompass: 1. Analyzing data 2. Categorizing data 3. Segregating tables 4. Assigning field names 5. Recognizing data types 6. Creating tables 7. Determining primary key components 8. Entering relevant data in tables 9. Creating as well as designing forms 10. Understanding queries 11. Generating along with designing reports 12. Final assessment (Slideshare Inc., 2013). Apart from the above discussed steps, there also exist certain significant aspects that are required to be taken into concern while creating a database. In this similar concern, these aspects comprise adoption along with execution of Database wizard, downloading a particular template and implementing a database object. The aspect of Database wizard aids in creating a database through generating a predetermined set of tables, forms, queries as well as reports. It is worth mentioning that the facet concerning downloading a template is duly considered to be one of the quickest ways of creating a particular database. In addition, the adoption as well as the execution of a database object helps to create a database by customizing a table and designing a query among others (Microsoft Corporation, 2013). Thus, on the basis of the above discussion, it can be affirmed that the aforementioned aspects play an imperative role in creating a database by a considerable level. References Hickey, E. J., McCrindle, B. W., Caldarone, C. A., Williams, W.G., & Blackstone, E. H. (2008). Abstract. Making Sense of Congenital Cardiac Disease with a Research Database: The Congenital Heart Surgeons' Society Data Center 2, pp. 152-162. Maimon, O., & Rokach, L. (n.d.). The KDD process. Introduction to Knowledge Discovery in Databases, pp. 1-17. Microsoft Corporation. (2013). Create an access database. Retrieved from http://office.microsoft.com/en-us/access-help/create-an-access-database-HP005187442.aspx Oracle. (2011). HITECH’s challenge to the health care industry. An Oracle White Paper, pp. 3-20. Russel, K. (2013). The benefits of a single database in care coordination throughout the continuum. Retrieved from http://www.beckershospitalreview.com/news-analysis/the-benefits-of-a-single-database-in-care-coordination-throughout-the-continuum.html Sewell, J., & Thede, L. Q. (2013). Handbook Informatics and Nursing: Opportunities and Challenges. United States: Lippincott Williams & Wilkins. Slideshare Inc. (2013). Steps of creating a database. Retrieved from http://www.slideshare.net/umerkhalidhabib/steps-ofcreatingadatabase University of Queensland. (2009). What is a database? UQL Cyberschool, pp. 1-2. University of Maryland. (2013). Using Boolean logic or connectors. Retrieved from http://www.lib.umd.edu/ues/guides/boolean-logic UMSL. (n.d.). Levels of data definition in databases. Database Management. Read More