REVIEWER FOR MIS.pdf

REVIEWER FOR MANAGEMENT INFORMATION SYSTEM (MIS) Management Information System (MIS) is an information system that evaluates, analyzes, and processes an organization's data to produce meaningful and useful information based on which the management can take right decisions to e...

REVIEWER FOR MANAGEMENT INFORMATION SYSTEM (MIS) Management Information System (MIS) is an information system that evaluates, analyzes, and processes an organization's data to produce meaningful and useful information based on which the management can take right decisions to ensure future growth of the organization. Data can be described as unprocessed facts and figures. It is the raw material that is organized, structured, and interpreted to create useful information systems. Information It is interpreted data; created from organized, structured, and processed data in a particular context. INFORMATION, KNOWLEDGE AND BUSINESS INTELLIGENCE Data − the raw material of information. - A Fact or a piece of information, or a series thereof. Information − Data organized and presented by someone. - Knowledge discerned from data. Knowledge − Information read, heard, or seen, and understood. Wisdom − Distilled and integrated knowledge and understanding or perceptions Business Intelligence − Information Management pertaining to an organization's policy or decision-making, particularly when tied to strategic or operational objectives. INFORMATION/DATA COLLECTION TECHNIQUES Surveys − A questionnaires is prepared to collect the data from the field. Secondary data sources or archival data: Data is collected through old records, magazines, company website etc. Objective measures or tests − An experimental test is conducted on the subject and the data is collected. Interviews − Data is collected by the system analyst by following a rigid procedure and collecting the answers to a set of pre-conceived questions through personal interviews. TYPES OF DATA In order to present the information in a proper manner to user , the data can be collected through two main methods – primary & secondary. Primary data collection refers to collecting original data or collecting data directly from the source. Secondary data collection refers to collecting data from secondary sources such as books , journals, researches reports, online databases, internet etc. COMPONENTS OF INFORMATION SYSTEMS Hardware – a component of the computer that we can physically see and touch that helps to process data and information inputted in the computer Software – a system that integrates applications that is use by the end-users Telecommunications - communication media & network support Human Resources/People - end users & IS specialists Data – raw materials, unprocessed information DATA PROCESSING - is the method of collecting raw data and translating it into usable information. It is usually performed in a step-by-step process by a team in an organization. The raw data is collected, filtered, sorted, processed, analyzed, stored, and then presented in a readable format. - is essential for organizations to create better business strategies and increase their competitive edge. By converting the data into readable formats like graphs, charts, and documents, employees throughout the organization can understand and use the data. 1. COLLECTION - The collection of raw data is the first step of the data processing cycle. The type of raw data collected has a huge impact on the output produced. Hence, raw data should be gathered from defined and accurate sources so that the subsequent findings are valid and usable. Raw data can include monetary figures, website cookies, profit/loss statements of a company, user behavior, etc. 2. PREPARATION - Data preparation or data cleaning is the process of sorting and filtering the raw data to remove unnecessary and inaccurate data. Raw data is checked for errors, duplication, miscalculations or missing data, and transformed into a suitable form for further analysis and processing. - to remove bad data (redundant, incomplete, or incorrect data) 3. INPUT - the raw data is converted into machine readable form and fed into the processing unit. This can be in the form of data entry through a keyboard, scanner or any other input source. 4. DATA PROCESSING - the raw data is subjected to various data processing methods using machine learning and artificial intelligence algorithms to generate a desirable output. This step may vary slightly from process to process depending on the source of data being processed (data lakes, online databases, connected devices, etc.) and the intended use of the output. 5. OUTPUT - The data is finally transmitted and displayed to the user in a readable form like graphs, tables, vector files, audio, video, documents, etc. 6. STORAGE - The last step of the data processing cycle is storage, where data and metadata are stored for further use. This allows for quick access and retrieval of information whenever needed, and also allows it to be used as input in the next data processing cycle directly. TYPES OF DATA PROCESSING 1. Manual Data Processing - is where data entry specialists record and process data manually through the ledger, paper record systems, and more manual data entry process. Though it is one of the earliest data processing methods, manual data entry is costly, time-consuming, error-prone, and labor- intensive. 2. Mechanical Data Processing - processes data through mechanical devices such as typewriters, mechanical printers, and other devices. 3. Electronic Data Processing - the use of spreadsheets to record student marks was prevalent during this time. Though this data processing method is accurate, reliable, and faster than its predecessor, it still required data specialists for manual data entry and calculations. 4. Batch Data Processing - process data by providing actions to multiple data sets through a single command. For example, in spreadsheets, data entry specialists can enter the formula for a single cell and apply it for the whole column. This type of data processing accelerates the processing time and can complete a series of tasks without human intervention. 5. Real-Time Data Processing - Real-time processing came into existence with the advent of the internet. By utilizing the internet, this processing method receives and processes data at the same time. Simply put, it captures data in real-time and generates quick or automatic reports. Hence this is one of the fastest data processing methods. For example, take GPS tracking systems where sensors detect heavy traffic and give input on a real-time basis. Though the process saves time and labor, it is expensive and requires heavy maintenance. 6. Online Data Processing - Online data processing is often confused with real-time data processing; both receive and process data simultaneously, but with online processing, the user can extract data anytime, anywhere. The bar code system is the best example of online processing. When buying a book in a bookstore, with the bar code scanning, the book’s data is automatically changed as sold. Another concrete example is access cards. 7. Automatic Data Processing - Data processing cannot be made better, with no human intervention, data entry on a real- time basis, error-free, and secure than any processing methods. - is the creation and implementation of technology that automatically processes data. This technology includes computers and other communications electronics that can gather, store, manipulate, prepare and distribute data. WORD PROCESSING - This is a software or an application where users can create and edit documents using this class of software. Functions include the ability to type and edit text, format fonts and paragraphs, as well as add, move, and delete text throughout the document. Files can be saved in a variety of electronic file formats like.doc,.docs, and.docx that is essential also for making reports and other documents. INFORMATION VS. DATA  Data can be described as unprocessed facts and figures. Plain collected data as raw facts cannot help in decision-making. However, data is the raw material that is organized, structured, and interpreted to create useful information systems.  Information is interpreted data; created from organized, structured, and processed data in a particular context.