Digital Marketing

BUSINESS INFORMATION SYSTEMS - A1 (Template Version)

Information technology focuses on (1) business skills and the use of technology to make decisions; (2) the selection, integration, and deployment of computing technology; and (3) technical skills, such as planning and deploying networking infrastructure, integrating databases, and building websites.   Data is raw, unprocessed information, such as numbers, text, or images, used as input for computer systems to generate meaningful insights.

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DETAILED INSTRUCTION

A/ ASSIGNMENT RECAP

  • Part 1 (Questions 1-5): Theories in the first four weeks

  • Part 2 (Questions 6-12): Excel functions

  • Part 3: Case study

 

B/ DETAILED GUIDELINES

  1. Part 1: Theories

  • Information technology focuses on (1) business skills and the use of technology to make decisions; (2) the selection, integration, and deployment of computing technology; and (3) technical skills, such as planning and deploying networking infrastructure, integrating databases, and building websites.  

  • Data is raw, unprocessed information, such as numbers, text, or images, used as input for computer systems to generate meaningful insights. 

For example: 5%, ISYS2056, RMIT, etc.

  • Information is processed and organized data that provides meaning or context, facilitating understanding and decision-making.

For example: ISYS2056 is the Business Information Systems Course.

  • Knowledge is the meaningful understanding and application of information, derived from the interpretation and synthesis of data.

For example: Business Information Systems is a core subject because its content is needed by all areas of business.

  • Forms of business analytics: Descriptive, Predictive, and Prescriptive.

  • Descriptive Analytics: focuses on summarizing historical data to provide insights into what has happened in a business. It involves reporting, scorecards and dashboards to describe past performance.

For example: The highest sales figure at Hammer Vacuum Cleaners in 2013 in WA was achieved by Joan.

  • Predictive Analytics: involves the use of statistical algorithms and machine learning techniques to forecast future outcomes based on historical data patterns. It helps businesses anticipate trends and make proactive decisions.

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