Management Informational System

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, a repository of data gathered from various sources, including corporate databases, summarized information from internal systems, and data from external sources. Analysis of the data includes simple query and reporting, statistical analysis, more complex multidimensional analysis, and data mining. Data analysis and data mining are a subset of business intelligence (BI), which also incorporates data warehousing, database management systems, and Online.

Data mining works or performs these feats using a technique that called modeling. Modeling is simply the act of building model in one application where there is an answer and then we apply it to another situation that you don’t. This act of model building has been doing by people for a long time, certainly it before the advent

The first generation of database systems were navigational, applications typically accessed data by following pointers from one record to another. The two main data models at this time were the hierarchical model, epitomized by IBM's IMS system, and the Network model and implemented

Data mining is the process through which previously unknown patterns in data were discovered. Another definition would be “a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify useful information and subsequent knowledge from large databases.” This includes most types of automated data analysis. A third definition: Data mining is the process of finding mathematical patterns from (usually) large sets of data; these can be rules, affinities, correlations, trends, or prediction models.

Data warehousing is defined as the design and implementation of processes and tools to manage and deliver complete, timely, accurate, and understandable data for decision making. It includes all the activities that make it possible for an organization to create, manage, and maintain a data warehouse or data mart (Williams & Williams, 2007). Data warehousing majorly deals with managing the development, the implementation, and the operation of a data warehouse or data store. It includes metadata management, data acquisition, data archiving, data cleansing, storage management, data integration, data distribution, security management operational

‘Data modelling is the process of defining what data is used in an information system or organization and how that data is organized. With Data model, the design of an information system is concerned mainly to optimize the data flow in the organization, and lead to new ways to produce, store, process and exchange data faster, more reliable and secure than previous practices.’

Data mining is the procedure of getting new patterns from large amount of data. Data mining is a procedure of finding of beneficial information and patterns from huge data. It is also called as knowledge discovery method, knowledge mining from data, knowledge extraction or data/ pattern analysis. The main goal from data mining is to get patterns that were already unknown. The useful of these patterns are found they can be used to make certain decisions for development of their businesses. Data mining aims to discover implicit, already unknown, and potentially useful information that is embedded in data.

Data mining generally is the process of analysing data from different perspectives and summarising it into useful information (Thuraisingham, 1999). It is also called the “Knowledge Discovery in Databases” process. It can be understand in the way of discovering interesting and useful patterns and relationships in large volumes of data. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for future use. (Han & Kamber, 2006)

Data mining is a set of automated techniques used for extracting hidden information and discovering useful patterns exist in the data sets.

The database is managed by a DBMS that provides for data retrieval (above), storage management, and transaction management.

Computers process data in a database into information, a database allows users to search information in an organized collection that is useful. In addition to documents, information can be in the form of audio, images, and video. With database software often called database management system (DBMS) users create a computerized database. DBMS users can add, modify, and delete data in the database; create forms and reports from the data in the database. Most organizations realize that data is one of their more valuable assets.

Data warehousing is a single repository or storage of data integrated from different sources which allows the business and the organization to generate a report or analysis to make decisions based on those data. Data warehousing is an integral part of any organization as it helps to increase the efficiency of the decision makers by integrating and transforming the data from multiple incompatible sources to the consistent and meaningful information which allows them to perform accurate, consistent and substantive analysis of data(P. 1152).

Data mining is often referred to as “analytical intelligence” and is helping organizations for a better view of their business, to understand their customer needs and increase the effectiveness of the organization in the long run.

Data is the most important component of the DBMS. The main purpose of DBMS is to process the data in efficient and convenient way for the users. In DBMS, databases are defined, constructed, modified , inserted and accessed from the database. There are two types of data in the DBMS. They are

The text book Data Warehousing concepts, techniques, products and applications by C.S.R. Prabhu. Mainly, the text book gives the information about the data model, online analytical processing systems and tools, data warehouse architecture, data mining algorithms, organizational issues of the data warehouse, data warehouse segmentation, Application of data mining and data warehousing. Firstly, the book describes Data Warehouse is a system where it is used for reporting the data from the wide range of the sources and indeed it helps the company to guide the management decisions. Moreover, Data Warehousing is the process where it evolved with the transformation and extraction of data from the various applications. Identically, it also has a technique from the formulation of the business intelligence where it gives effective implementation which makes the Data warehouse the effective technology for the business use. Importantly, Data Warehouse is the division of data into the individual data component. Similarly, Data Warehouse helps to analyze the data and whereas they are technologies which helps to analyze the data available in the data warehouse. Indeed, the functions of the Data Warehouse tools are data extraction, data cleaning, data transformation. Mainly, the data extraction gathers the data from the multiple sources, data cleaning helps to find and correct errors in data, data transformation converts the data into data warehouse format. Consequently, data cleaning and