ANSWERS :
Differences between Database Management System (DBMS) and Information Retrieval System (IRS).
DATABASE MANAGEMENT SYSTEM (DBMS)
FUNCTIONALITIES INFORMATION RETRIEVAL SYSTEM (IRS)
1. Ability to updating and retrieving data. 1. Identify the information (sources) relevant to the areas of interest for the target users community
2. Support current updates 2. Analyzing the contents of the sources
3. Recovery of data 3. Representing the contents of the analyzed sources in a way that will be suitable for matching users queries
4. Security management 4. Analyzing users queries and to represent them in a form that will suitable for matching with the database
5. Data integrity management 5. Match the search statement with the stored database
6. Data transformation and presentation 6. Retrieved the information that is relevant
7. Data storage management 7. Make necessary adjustment in the system based on feedback from the users
Database Management System (DBMS)
1. Ability to update and
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It is difficult to know where to find insights hiding in unstructured data sets without the structured data.
• To arrange data in a particular manner. These manners or set of rules is defined in the data structure so that the data used in computer systems can properly use at necessary time. • Unstructured data enhances a business ability to derive greater insight from the data sets. Because people will try to identify all unstructured data through the business ability and may change it to structured data so that it can be useful for the business.
• It is tools that are widely accessible today, it helps businesses use this data to its greatest potential. Is a valuable piece to the data pie of any business.
Examples • Databases
• XML data
• Data warehouses
• Enterprise systems (CRM, ERP) • Excel spreadsheets
• Word documents
• Email messages
• RSS feds
• Audio files
• Video
Other data structures can be implemented like different types of data structures like graphs, queues and trees. (Kakria, 2017) It brings variables together that are of the same type and groups them together for the purpose of efficient coding. Data may be stored in the elements of an array. It can also be manipulated as the same way as normal variables.
1.Explain why you choose your target area and why the target audience is relevant to this particular area. Use statistics and recent examples to your answer.
The first type of Big Data used in military logistics is the structured data, which is data that has been stored in the databases in an orderly manner. In military logistics, the two sources of structured data are machines and humans. Examples include GPS data, usage statistics of vehicles, ships and aircrafts, and data from medical devices. The second type of structured data is unstructured data, which is data that resides in the traditional column databases and have no clear format in storage. Examples include the mobile data, and data from satellite images about certain terrains (Sagiroglu & Sinanc, 2013).
Data can give you quite a bit of information about your customers. By examining it, you will be able to begin to see patterns and learn the habits of your customers. This could mean that you are able to provide the correct number of products at the perfect time instead of having a shortfall or being left with additional stock long after interest has fallen in the product.
Business Intelligence, often coined as 'decision support' or 'CRM analytics'. When business intelligence is aligned with CRM software and consumer strategies, it enables decision-maker and entrepreneurs of an organization to understand, identify, analyze and forecast any situation much better. BI tools transform raw data into information and use it to drive an intelligent business. This insight is well accessed by the top level employees of the company when they need it to improve the accuracy of the company performance Priority goal: Future vision The rise of BI technologies provides an in-depth knowledge of how the management can use the collected data.
It allows the analyst to work with a small, manageable amount of data in order to build and run analytical model quickly, while still drawing accurate finding. Sampling can be particularly useful with data sets that are too large to efficiently analyze in full. • feedback on results: both staffs and customers can provide the required feedback for the business improvement and ideas contributions. Therefore their opinions and ideas are used to make the required adjustments for the further business performance improvements. • peer review: Peer review help validating researches, establish a tool by which it can be evaluated, and increase networking possibility within research groups.
[7] Elmasri & Navathe. Fundamentals of database systems, 4th edition. Addison-Wesley, Redwood City, CA. 2004.
Currently, businesses want to use the information effectively for competitive advantage to make better decisions that improve and optimize business processes, predict the market dynamics accurately, optimize forecasts to adequately maintain resources to name a few reasons.
Data is collected and the patterns are recognized, in order to understand the physical properties, and further to visualize the data as
"Data mining is the process of discovering meaningful new correlations, patterns, and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques" (SPSS). However, really data mining turns databases into knowledge bases which is one of the fundamental components of expert systems. Instead of the computer just blindly pulling data from a database, the compu...
Determine the central ideas or information of a primary or secondary source; provide an accurate summary that makes clear the relationships among the key details and ideas.
The database application design can be improved in a number of ways as described below:
It is more focuses on the process instead of the individual. It acknowledges both internal and external customers, It helps to improve the need for objective data to analyze and the processes.
Example of the non-structured data is an email and the word processing documents. An email is the message that being distributed into the recipients using an electronic. It is being sent from one computer user to another user. Example of the word processing documents is the Microsoft excel. It is spreadsheets that being produce by the Microsoft for calculating, graphic tools, pivot tables and a macro programming language. This is because the files may have internal structure but it is considered as the non-structured data because the data in the database is still unstructured.
The main aim of this project is to research on the integration of “Natural Language Processing “ and information systems engineering to enhance query retrieval in natural language processing.