Unit 17: business process support is the significant program of computing in the HND diploma focusing on the critical character of information and data in the decision-making of organisation and problem-solving. In the process of business, meaningful information and accurate data are the significant drivers that form the foundation for useful operations. Business intelligence greatly depends on data science which uses techniques and tools for versatile purposes including data integration, data mining, data warehousing and data quality management. These methods enable the organisation to transform the raw data into valuable information with the support of their system of information management and improve their potential to make informed decisions.

With the help of this unit, the learners will identify the significant techniques technology and tools which assist them in the interpretation process and collection of data to generate information with great meanings. This phenomenon is significant for supporting the functions of Business and improving the efficiency of operations. The identification of the way through which data science identifies the problems of the real world makes students acquire the significance of Sourcing and turning data into crucial information which drives decision-making. They also identify the data science emergence and its application in business process Optimisation. It also equips them with the potential to apply these practical techniques to solve the challenges of business.

At the end of the unit, the learners will increase their deep appreciation for the data value strategies in the performance of the organisation and its Optimisation. With the help of this exposure to the methodology and relevant Technology, they recognised the way through which these elements contribute to the efficient process of Business and decision-making. Moreover, learners generate crucial skills including critical thinking analysis and communication that are significant for academic and Employment success. This unit makes them prepare to contribute and navigate efficiently in the environment of data drive in business. It provides a robust foundation in both analytical and Technical potential crucial for the computing of a career.

Unit Objectives

The main objectives of unit 17: business process support are associated with the learning domains in computing of the HND diploma.

• To equip students with information and data recognition and its character in decision-making and supporting the process of business.
• To familiarise the learners with methods and tools including data integration, data mining, and data warehousing for the transformation of raw data into Useful information.
• To apply the techniques of science in scenarios of the real world, solving the problems of business and improving the efficiency of processes.
• To cultivate crucial skills including critical thinking, communication, and analytical reasoning to make learners prepare for further academy and employment in the field of computing.

Learning Outcomes

The learning outcomes are the main deal of the assignment in unit 17: business process support for Computing Learners.

LO1: Discuss the use of data and information to support business processes and the value they have for an identified organisation.

• Information and data in an organisation
• Importance of information and data for organisations that include decision making (tactical, operational, and strategic), improving and deliver services, Efficiency and optimise of workflow, increasing in margins of profit, reducing overheads, diversification.
• Categories of data utilised by organisations that include unstructured and structured data.
• Influence on the process of business related to storage and elicitation
• The significance of impact and reliable data on businesses
• The use of information and data for supporting the process of business
• Analysis of the trends of the market for pattern identification
• Factors influence in own demand and supply of good prices
• System of monitoring for Performance matrix
• Controlling and monitoring the product or service quality
• Analysis of user levels or interaction of customers with engagement
• Identification of trends in purchasing and browsing for the target purpose of marketing

LO2: Discuss the implications of the use of data and information to support business processes in a real-world scenario.

• Ethical legal and social implications
• Identify the ethical social and professional issues in terms of the use of data and information for supporting the process of business. For example, the way through which information is used or collected, consumption of cookies and other data transactions, and data sharing for example services organisations and departments.
• Regulatory and legal problems in terms of the data and information used for supporting the process of business in terms of recent principles and legislation of goods practice according to the computing professional body recommendation
• Management of cyber security
• Information and data for example external and internal threats.
• Human behaviour influences on cyber security such as opportunity and the bay of motivation to generate a threat
• Secure by design concept when using and developing the systems for handling the information and data
• Procedure to mitigate the common data and information threats at information and personal levels.
• Implications of organisation of failing the appropriate protection of information and data for example financial implications legal actions descriptions of reduction and operations in the damage and productivity to public image.

LO3: Explore the tools and technologies associated with data science and how it supports business processes.

• Overview of data science
• Identify the way through which the exceptional amount of data generated growth influences on the way through which the data is used and collected
• The significant aim of data science that include data making with retrieval and useful actionable intelligence extraction for improving the performance of business, implementation extraction and automation.
• Significant roles of job that include data scientist and data engineer And the way through which they work on the members of the team, for example, business senior managers data analyst software engineers in the development and change of lifecycle
• Skills related to data science that include statistics and mathematics, scripting and programming skills, integration and investigation of data, significant knowledge of business.
• Data science sub-discipline in the fields that include machine learning, data engineering, and artificial intelligence.

LO4: Demonstrate the use of data science techniques to make recommendations to support real-world business problems.

• The business process support includes the techniques for user and illicit requirements, requirements of the system, and automated procedure applications including the appropriate time to use.
• Tools designing, package or program which can perform a particular task for supporting the solution of problem or decision making such as The E-Commerce functions for the website to support the analysis of A purchase, Dashboard of the user for investigating the particular market trends.
• Modelling and analysis of the process of business utilising relevant techniques, software tools, notation, and Standards.
• User requirements for example functional interface and user interface, considerations of interaction and user management, resolve risk or mitigate risk, meaningful output data, set as factory system requirements and user requirements customisation.

Assessment Criteria

The main association of the learning outcomes of unit 17: business process support is with the assessment criteria.

LO1: Discuss the use of data and information to support business processes and the value they have for an identified organisation.

• 1.1 Discuss how data and information support business processes and the value they have for organisations.
• 1.2 Discuss how data is generated and the tools used to manipulate it to form meaningful data to support business operations.
• 1.3 Assess the value of data and information to individuals and organisations in relation to real-world business processes.
• 1.4 Evaluate the wider implications of using data and information to support business processes in an identified organisation.

LO2: Discuss the implications of the use of data and information to support business processes in a real-world scenario.

• 2.1 Discuss the social legal and ethical implications of using data and information to support business processes.
• 2.2 Describe common threats to data and how they can be mitigated at on a personal and organisational level.
• 2.3 Analyse the impact of using data and information to support business real-world business processes.

LO3: Explore the tools and technologies associated with data science and how it supports business processes.

• 3.1 Discuss how tools and technologies associated with data science are used to support business processes and inform decisions.
• 3.2 Assess the benefits of using data science to solve problems in real-world scenarios.
• 3.3 Evaluate the use of data science techniques against user and business requirements of an identified organisation.

LO4: Demonstrate the use of data science techniques to make recommendations to support real-world business problems.

• 4.1 Design a data science solution to support decision-making related to a real-world problem.
• 4.2 Implement a data science solution to support decision-making related to a real-world problem.
• 4.3 Make justified recommendations that support decision-making related to a real-world problem.

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