Task 2 Data Quality Issues And Remedies 10 Marks Discuss Both The Generic Issues That Data Analysts Encounter In Sour 1 (50.08 KiB) Viewed 36 times
Task 2 Data Quality Issues And Remedies 10 Marks Discuss Both The Generic Issues That Data Analysts Encounter In Sour 2 (38.85 KiB) Viewed 36 times
Task 2: Data quality issues and remedies (10 marks) Discuss both the generic issues that data analysts encounter in sourcing, reviewing and cleansing data and also specific issues with the project data that BUJ has provided and how you propose to address those issues. Guidelines: • List and explain generic data problems and how to identify them. What are the different options for resolving these generic issues? • List all the data problems you have identified with the BU dataset. Explain how you identified the problems and how you propose to address them. Page 5 of 13 BPP UNIVERSITY SCHOOL OF BUSINESS AND TECHNOLOGY Task 3: Data analysis and commentary (20 marks) Set out and explain the results of your numeric data analysis in the form of tables, summary data and supporting commentary. Explain how your results inform understanding of BIJ's performance and business operations. This should include three tables setting out: (Table A) Data and trends in sales volume and value by month, by year and across the whole analysis period (Table D) Benchmark comparisons of category performance covering sales volume and value by quarter, by year and across the whole analysis period, and (Table C) Benchmark comparisons of sales volume and value between markets by quarter, by year and across the whole analysis period. Guidelines: • Include summary exploratory data calculations, for example trend data, top and bottom performing categories, ranges, averages, standard deviations; top and bottom performing time periods • Ensure your tables are professionally presented: Headings, units, data formats. Highlight and annotate key data elements • For each table include firstly an explanation of the table and its contents and then a bullet- point list of what you can see or infer from the data.
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