Write a 1500 words report on the importance and use of predictive analytics technologies/tools

Write a 1500 words report on the importance and use of predictive analytics technologies/tools in one of the following sectors. Free from plagiarism and the use of AI tools 1. Retail Sector 2. Financial Sector 3. Energy Sector 4. Education Sector Please follow the Harvard Referencing Handbook 1,500 words, not counting spreadsheet extracts and graphs pasted in. The first page should be the Cover page; The second page should have an executive summary noting what problem statement and question you sought to work on and what your analysis suggests in that context. The third page should have a table of contents. The report should focus on the analysis of the adoption and implication of predictive Analytics in your chosen sector, highlighting the resultant change in the sector. A brief description of the adoption process or steps should be included in the report, including the details of time, costs and other critical aspects of adoption like training. Participants can use an example of a company in their chosen sector to elaborate on the adoption process, including the details of time and costs. Based on your analysis, present your recommendations for the companies ready to adopt predictive analytics in your chosen sector. The report should demonstrate the following knowledge: The meaning and importance of predictive analytics; Key enabling technologies of prediction; Methods of prediction; Machine learning and prediction; Outcomes to be achieved and demonstrate the following skills: • The application and evaluation of Predictive Analytics Technologies in a variety of contexts in organisations • To critically appraise the appropriateness of specific Predictive Analytics Technologies for different business contexts; • To critically appraise the appropriateness of specific data sources, structures and types for specific Predictive Analytics Technologies; • To identify the appropriate underlying method of prediction, e.g. information based, similarity-based, probability-based and error based; • To identify the underlying method of prediction built into specific Predictive Analytics Technologies; • To consider human systems that are involved in applying the different methods of predictive analytics; Develop skills developing applications in Predictive Analytics, including: Creating and using data sources for prediction; Training machines to learn; Transforming data for machine learning; Interpreting predictions; Managing machine learning objects; Monitoring machine learning with metrics; To develop and justify business and project plans for machine learning; To identify strategically important machine learning applications in organisations; To assess ‘Digital Business’ as a discipline and as a field of practice, in providing innovation and change in a range of existing or potential client organizations; To apply consultation and mentoring methods in a Digital Business. • Control and prediction; • The contemporary technologies of prediction; • Methods for implementing predictive technologies projects; • Assessment of strategic value of predictive technologies. • To provide foundational knowledge of Predictive Analytics Technologies (‘PAT’) for application in organisations and businesses; • To develop the required skill-set to critically construct Predictive Analytics Technologies change projects; • To critically appraise the application of the use of Predictive Analytics Technologies across different organisations and contexts. Illustrates an excellent level of understanding of complex issues in the report. All work requirements are dealt with to a high standard, and the work is free from all but isolated minor errors. The material is wholly relevant to the tasks. Excellent analysis, synthesis and critical reflection with the ability to tackle issues and questions not previously encountered. Evidence of independent and original judgment concerning resolving the client’s needs and problems. Excellently presented in terms of structure and professional style.