Using the Customer Sales list shown above Identify and describe at least three of the following...
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Using the Customer Sales list shown above Identify and describe at least three of the following issues that deal specifically with the structure of the database table: a) Any problems with unnecessarily repeated (i.e. redundant) data. b) Any problems with atomicity -that is columns that store more than one piece of information. For example: multiple dates, multiple names, or multiple pieces of address information. c) Any NULL values (if any). d)Any groupings of columns that really belong in separate tables because they really describe different entities. Question#2 Try to separate out all of the information stored in the above Customer Sales list into include only columns from the Customer Sales list that really belong to that new table. For example, the new Invoice table should only contain columns from the Book List that describe invoice specific attributes (e.g. Invoice#). The Product table should only include columns that really describe something about the product and the Customer table should only include customer information from the original Customer Sales list. In your listing of the new tables you do not have to list all the data in the Customer Sales list only the column headings. A few things to watch out for: 1. Make sure all the columns in your new tables are split up properly so they are atomic (i.e. store only one piece of information). 2. Make sure you clearly identify a primary key (i.e. a unique lookup) on every new table (it is ok to make up a new column if you want). 3. It is ok to rename or split up the original columns from the Customer Sales list but you cannot exclude away ANY of the original columns (for example, you cannot just exclude the Loyalty Program column). Sample New Table Listing for Invoice: Invoice (Invoice#, etc...) Primary Key: Invoice# NOTE: The etc... here denotes the rest of the properly associated, atomic columns that should be grouped under their correct table. You should not have the same column in more than one table! Task Invoice# Sales Total with Tax #Units Ordered $26,400 $13,200 $28,800 $14,400 101 102 103 104 105 106 107 108 109 110 $6,000 $3,000 $6,000 $14,400 $14,400 $28,800 Customer Sales Item Name 10 CAD Workstations 5 CAD Workstations 20 Staff Laptops 10 Staff Laptops 10 Laser Printer 5 Laser Printer 10 Laser Printer 10 Staff Laptops 10 Staff Laptops 20 Staff Laptops Item ID# Price per Unit Customer Name 11 11 12 $2,200 Ho Associates $2,200 Wayne Corp. $1,200 Ho Associates $1,200 Wayne Corp. $500 Eagle Industries $500 Ho Associates $500 Eagle Industries $1,200 Eagle Industries $1,200 Eagle Industries $1,200 Wayne Corp. 05555533 12 10 10. 10 12 12 12 Credit Limit Customer Location Loyalty Program $300,000 Bellevue, WA 2020-2022 $400,000 Kirkland, WA 2021- $300,000 Bellevue, WA 2020-2022 $400,000 Kirkland, WA 2021- $100,000 Richmond, VA 2020-2021 $300,000 Bellevue, WA 2020-2022 $100,000 Richmond, VA $100,000 Richmond, VA $100,000 Richmond, VA $400,000 Kirkland, WA 2020-2021 2020-2021 2020-2021 2021. Using the Customer Sales list shown above Identify and describe at least three of the following issues that deal specifically with the structure of the database table: a) Any problems with unnecessarily repeated (i.e. redundant) data. b) Any problems with atomicity -that is columns that store more than one piece of information. For example: multiple dates, multiple names, or multiple pieces of address information. c) Any NULL values (if any). d)Any groupings of columns that really belong in separate tables because they really describe different entities. Question#2 Try to separate out all of the information stored in the above Customer Sales list into include only columns from the Customer Sales list that really belong to that new table. For example, the new Invoice table should only contain columns from the Book List that describe invoice specific attributes (e.g. Invoice#). The Product table should only include columns that really describe something about the product and the Customer table should only include customer information from the original Customer Sales list. In your listing of the new tables you do not have to list all the data in the Customer Sales list only the column headings. A few things to watch out for: 1. Make sure all the columns in your new tables are split up properly so they are atomic (i.e. store only one piece of information). 2. Make sure you clearly identify a primary key (i.e. a unique lookup) on every new table (it is ok to make up a new column if you want). 3. It is ok to rename or split up the original columns from the Customer Sales list but you cannot exclude away ANY of the original columns (for example, you cannot just exclude the Loyalty Program column). Sample New Table Listing for Invoice: Invoice (Invoice#, etc...) Primary Key: Invoice# NOTE: The etc... here denotes the rest of the properly associated, atomic columns that should be grouped under their correct table. You should not have the same column in more than one table! Task Invoice# Sales Total with Tax #Units Ordered $26,400 $13,200 $28,800 $14,400 101 102 103 104 105 106 107 108 109 110 $6,000 $3,000 $6,000 $14,400 $14,400 $28,800 Customer Sales Item Name 10 CAD Workstations 5 CAD Workstations 20 Staff Laptops 10 Staff Laptops 10 Laser Printer 5 Laser Printer 10 Laser Printer 10 Staff Laptops 10 Staff Laptops 20 Staff Laptops Item ID# Price per Unit Customer Name 11 11 12 $2,200 Ho Associates $2,200 Wayne Corp. $1,200 Ho Associates $1,200 Wayne Corp. $500 Eagle Industries $500 Ho Associates $500 Eagle Industries $1,200 Eagle Industries $1,200 Eagle Industries $1,200 Wayne Corp. 05555533 12 10 10. 10 12 12 12 Credit Limit Customer Location Loyalty Program $300,000 Bellevue, WA 2020-2022 $400,000 Kirkland, WA 2021- $300,000 Bellevue, WA 2020-2022 $400,000 Kirkland, WA 2021- $100,000 Richmond, VA 2020-2021 $300,000 Bellevue, WA 2020-2022 $100,000 Richmond, VA $100,000 Richmond, VA $100,000 Richmond, VA $400,000 Kirkland, WA 2020-2021 2020-2021 2020-2021 2021.
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Auditing A Practical Approach with Data Analytics
ISBN: 978-1119401742
1st edition
Authors: Raymond N. Johnson, Laura Davis Wiley, Robyn Moroney, Fiona Campbell, Jane Hamilton
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