[SOLVED] COMM1822 Consultation

Introduction to Databases for Business Analytics
Subqueries and Merge Statements Big Data
Lecturer-in-Charge: Kam-Fung (Henry) 2 2022
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Week 9 Welcome Video

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Acknowledgement of Country
UNSW Business School acknowledges the Bidjigal (Kensington campus) and Gadigal (City campus) the traditional custodians of the lands where each campus is located.
We acknowledge all Aboriginal and Islander Elders, past and present and their communities who have shared and practiced their teachings over thousands of years including business practices.
We recognise Aboriginal and Islander peoples ongoing leadership and contributions, including to business, education and industry.
UNSW Business School. (2022, May 7). Acknowledgement of Country [online video]. Retrieved from https://vimeo.com/369229957/d995d8087f

COMM1822 Consultation
Consultation with the LiC
Kam-Fung (Henry)
10.00 11.00 am (AEST)
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COMM1822 PASS Class
PASS Class

10:00 11:00 am (AEST)
Online via
https://au.bbcollab.com/guest/734c9 39b0ddf42d2868fc2304b801d82

MyExperience
Discussion of Subqueries and Merge Statements Week 9 Sandbox Activity
Big Data Strategy

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MyExperience
Discussion of Subqueries and Merge Statements Week 9 Sandbox Activity
Big Data Strategy

Week 9 Lab Manual Discussion
1. What is the purpose of subqueries and how might they be useful?
2. What are the different types of subqueries?
3. What new concept has been introduced?
4. What new clauses have been introduced?

MyExperience
Discussion of Subqueries and Merge Statements Week 9 Sandbox Activity
Big Data Strategy

Week 9 Sandbox Activity
1. Determine which other customer visited the restaurant on the same day as.
2. Determine which food items have a longer preparation time than Ox Tongue.
3. Determine which food items cost less than the most frequently ordered drink item. Display the name of the dish and the price.
4. List each chefs name, and the average price of all items ordered that each chef prepares (per day).

Week 9 Sandbox Activity
1. Determine which other customer visited the restaurant on the same day as.
SELECT DISTINCT c.name FROM CUSTOMER c INNER JOIN ORDERS o USING (customer_id) WHERE order_date =
(SELECT order_date FROM ORDERS WHERE customer_id =
(SELECT customer_id FROM CUSTOMER where name = )
AND c.name <> ;

Week 9 Sandbox Activity
2. Determine which food items have a longer preparation time than Ox Tongue.
FROM FOOD WHERE cook_time >
(SELECT cook_time FROM FOOD WHERE dish_name = Ox Tongue);

Week 9 Sandbox Activity
3. Determine which food items cost less than the most frequently ordered drink item. Display the name of the dish and the price.
SELECT * FROM FOOD WHERE price <SELECT d.priceFROM DRINKS d INNER JOIN ORDERS o ON d.drink_id = o.drink_idGROUP BY d.drink_id, d.drink_name, d.priceORDER BY count(*) DESCFETCH FIRST 1 ROWS ONLY — Can be done alternatively using more subqueries to get themaximum count, then join back ); Week 9 Sandbox Activity4. List each chefs name, and the average price of all items ordered that each chef prepares (per day).SELECT c.name, TO_CHAR(av.average_revenue, ‘$99.99’) “Average Daily Revenue” FROM CHEF cINNER JOINSELECT staff_id, AVG(daily_revenue) average_revenue FROM(SELECT c.staff_id, o.order_date, sum(f.price*(100 – d.percentage)/100.0) daily_revenue FROM orders o INNER JOIN discounts dON o.discount_id = d.discount_idINNER JOIN food fON o.food_id = f.food_idINNER JOIN cooks cON f.food_id = c.food_idGROUP BY c.staff_id, o.order_date) GROUP BY staff_idav ON c.staff_id = av.staff_id; Online Safety – Break Rest Breaks: https://safety.unsw.edu.au/office-safety-toolkit/rest-breaks WorkRave at UNSW: https://safety.unsw.edu.au/sites/default/files/documents/UNSW_WorkRave_ V1.0.pdf Setting up you Workstation : https://safety.unsw.edu.au/setting-your- workstation-video Online Safety and Wellbeing Tutorial: https://student.unsw.edu.au/safety SafeWork 6 Simple stretches: https://www.safework.nsw.gov.au/resource- library/six-simple-stretches Take a 5 minute break MyExperience Discussion of Subqueries and Merge Statements Week 9 Sandbox Activity Big Data Strategy Big Data Strategy (Discussion)1. Research a company of your choice (different from last weeks company if possible)2. Build a Big Data strategy using the 5 steps of the Enterprise Big Data Framework: https://www.bigdataframework.org/formulating-a-big-data- strategy/3. Focus in this discussion on the challenges each Big Data project would face, i.e., the three interdependent components that cause success or failure: People, Process and TechnologySee next slide30 min in breakout rooms/groupsPresent your work in groups (3 min per group)https://www.bigdataframework.org/formulating-a-big-data-strategy/ CS: assignmentchef QQ: 1823890830 Email: [email protected]