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First of all, have a look at the SQL database creation and population code that accompanies this assignment in the furniturestore_sql.txt file. You should be familiar with the fields and what kinds of data are represented in the database.
You must include all SQL code here in the spaces below, respecting standard capitalization conventions as presented in the tutorials. For ease of review, please use BOLD on any SQL code (see the example below). For certain responses you must also include a ‘snip’ / screenshot of your results. If you can, try not to take an image of the entire screen, but only of the relevant output.
IFSM 330 Business Intelligence and Data Analytics
Business Intelligence SQL Assignment Instructions
Student Name:
First of all, have a look at the SQL database creation and population code that accompanies this
assignment. You should be familiar with the fields and what kinds of data are represented in the
database. All questions and items in this assignment pertain to the SQL code that accompanies this
assignment.
You must include all SQL code here in the spaces below, respecting standard capitalization conventions
as presented in the tutorials. For ease of review, please use BOLD on any SQL code (see the example
below). Your SQL code must be in text format, so that the instructor can cut and paste for review and
testing purposes. Here is an example of SQL code/text that can be cut and pasted for testing:
CREATE TABLE customers (id INTEGER PRIMARY KEY, name TEXT, age INTEGER, weight REAL);
INSERT INTO customers VALUES (73, “Brian”, 33, 50);
For certain responses you are also asked to include a ‘snip’ / screenshot of your results. If you can, try
not to take an image of the entire screen, but only of the relevant output.
You should use sqliteonline.com to complete this assignment, both to test code and take screenshots:
https://sqliteonline.com/
Here is an example of a database schema image and a query results image from sqliteonline.com.
Due to screen resolution, it’s not always possible to capture all query results. But be sure your images
are legible, no smaller than the second image below. If an image is not legible, your assignment may
be returned to you and you’ll have to rerun the SQL scripts.
Feel free to take several screenshots as needed or make the columns narrower in the sqliteonline
output before taking the screenshot (columns can be manually made more narrow by hovering over
the lines marked in red below):
For some of these questions, you will need to perform a SUM or AVERAGE in a grouphttps://www.khanacademy.org/computing/computer-programming/sql/more-advanced-sqlqueries/pt/restricting-grouped-results-with-having
1). 10 points. As you glance through the database, you note that Houston is spelled with a lower case
‘h’ in at least one case. First of all, write the SQL code to list all values for Houston, capitalized or not
capitalized. Begin with SELECT * FROM sales to list all fields.
Then, write the SQL script to update all lower case instances of houston to Houston. NOTE: use of
WHERE id= is not permitted. This method is used in the tutorial but is not practical if you had a very
large database.
2) 10 points. Write an SQL query to list all products and the total sales in dollars for each product. List
products in order from highest total sales to lowest. Use Total_Sales as the label for the field (column)
containing the sales data.
INSERT a snip (image) of your QUERY RESULTS here:
3) 10 points. Write an SQL query to list the customer name and the dollar amount of total purchases.
List only names and dollar amounts if total purchases exceed $5000. List in order of total purchases
from highest to lowest and use the column titles Customer_Name and Total_Purchases.
INSERT a snip (image) of your QUERY RESULTS here:
4) 10 points. Write an SQL query to list the states (note Canadian provinces are also included in the
database) and the dollar amount of the average purchase. List only states (and provinces) when the
average purchase exceeds $2500. List in order of average purchase from highest to lowest and use the
column titles State_Province and Average_Purchase. Round the dollar amount of the Average_Purchase
so only whole numbers (no decimals) will appear.
INSERT a snip (image) of your QUERY RESULTS here:
5a) NOTE: For all of Q5, this must be an actual situation/scenario that can be executed with an SQL
query on the data provided in the assignment. NOT a hypothetical scenario or partial SQL query. If
this is unclear, please ask.
15 points. In 2-3 sentences, given the nature and structure of the furniturestore.sql data, describe a
situation or scenario (or question that might be answered) that would require use of a CASE statement
in SQL. (This is a very open question with many correct responses. Think about what the CASE
statement in SQL allows us to do.)
5b) Create the SQL query for the scenario presented in part a). This SQL query must be complete,
executable and produce output relevant to the scenario presented in part a).
INSERT a snip (image) of your QUERY RESULTS here:
6a) 15 points. You have been asked to produce a report that shows all chairs bought on January 12,
2019. In the box below, respond to the following question:
Why does the following SQL query not yield any results (feel free to test it)?
SELECT * FROM sales WHERE product = ‘Chair’ AND transaction_date = ‘1/12/19’;
6b) Rewrite the query so that it yields the correct results.
INSERT a snip (image) of your QUERY RESULTS here:
PART 2:
Part 2 introduces a second table to the database schema. When creating queries from two tables, in
particular when there may be a field that shares a common name, it is safer to construct your queries
with the table name AND field name. You may wish to review the “JOINing related tables” tutorial and
video on Khan Academy.
7) 5 points. Using an SQL script, add (CREATE) a suppliers table to the database schema, with an
autoincrement integer as the primary key (id), and fields for name and country (both text). The primary
key (id) will correspond to the supplier field in the sales table (e.g. supplier in sales is a foreign key).
8) 5 points. Using an SQL script, insert the following data into the suppliers table, in the order presented
in the table (Reminder: id primary key should have been set to autoincrement when the table was
created):
Name
Ikea
Rosewood
BoConcept
AllModern
Country
Sweden
Thailand
Denmark
United States
9) 10 points. Write an SQL query to list transaction date, customer name, product, price, supplier name
and country (6 columns) ordered by price from highest to lowest. List only items with a price greater
than 1500. Construct the SQL query to present field (column) titles as: Date, Customer, Product, Price,
Supplier, Country.
INSERT a snip (image) of your QUERY RESULTS here:
10) 10 points. Write an SQL query to list supplier name, country and total sales for that supplier.
INSERT a snip (image) of your QUERY RESULTS here:
Insert (copy and paste) all code from Items 7-10 within this textbox:
/*
Sales from an online furniture store
Collected by: https://www.khanacademy.org/profile/charlesb2000/
Modified and redistributed per Khan Academy Terms of Service 5.3: https://www.khanacademy.org/about/tos#5 (MIT License)
*/
CREATE TABLE sales(
ID INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT
, transaction_date TEXT
, product TEXT
, price INTEGER
, payment_type TEXT
, name TEXT
, city TEXT
, state TEXT
, country TEXT
, account_created TEXT
, last_login TEXT
, latitude REAL
, longitude REAL
, supplier INTEGER
);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 4:53′,’Chair’,1200,’Visa’,’Bettina Schmidt’,’Parkville’,’MO’,’United States’,’1/2/19 4:42′,’1/2/19 7:49′,39.195,-94.68194,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 13:08′,’Chair’,1200,’Mastercard’,’Federica Villanueva’,’Astoria’,’OR’,’United States’,’1/1/19 16:21′,’1/3/19 12:32′,46.18806,-123.83,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/4/19 12:56′,’Couch’,3600,’Visa’,’Gerd Winslow’,’Cahaba Heights’,’AL’,’United States’,’11/15/18 15:47′,’1/4/19 12:45′,33.52056,-86.8025,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/4/19 13:19′,’Chair’,1200,’Visa’,’Laurence Arabia’,’Mickleton’,’NJ’,’United States’,’9/24/18 15:19′,’1/4/19 13:04′,39.79,-75.23806,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/4/19 20:11′,’Chair’,1200,’Mastercard’,’Fleur Barnes’,’Peoria’,’IL’,’United States’,’1/3/19 9:38′,’1/4/19 19:45′,40.69361,-89.58889,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 20:09′,’Chair’,1200,’Mastercard’,’Adam Martin’,’Martin’,’TN’,’United States’,’1/2/19 17:43′,’1/4/19 20:01′,36.34333,-88.85028,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/5/19 2:42′,’Chair’,1200,’Diners’,’Stacy Rourke’,’New York’,’NY’,’United States’,’1/5/19 2:23′,’1/5/19 4:59′,40.71417,-74.00639,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 9:16′,’Chair’,1200,’Mastercard’,’Sean Davis’,’Shavano Park’,’TX’,’United States’,’1/2/19 8:32′,’1/5/19 9:05′,29.42389,-98.49333,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/5/19 10:08′,’Chair’,1200,’Visa’,’Georgia Winston’,’Eagle’,’ID’,’United States’,’11/11/18 15:53′,’1/5/19 10:05′,43.69556,-116.35306,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 14:18′,’Chair’,1200,’Visa’,’Richard Parker’,’Riverside’,’NJ’,’United States’,’12/9/18 12:07′,’1/5/19 11:01′,40.03222,-74.95778,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/5/19 11:37′,’Chair’,1200,’Visa’,’Janet Feinbaum’,’Ottawa’,’ON’,’Canada’,’1/5/19 9:35′,’1/5/19 19:24′,45.4166667,-75.7,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 7:35′,’Chair’,1200,’Diners’,’Hani Mercer’,’Salt Lake city’,’UT’,’United States’,’12/30/18 5:44′,’1/6/19 10:52′,40.76083,-111.89028,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/6/19 7:18′,’Chair’,1200,’Visa’,’Asuman Winters’,’Chula Vista’,’CA’,’United States’,’1/6/19 7:07′,’1/7/19 7:08′,32.64,-117.08333,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/1/19 2:24′,’Chair’,1200,’Visa’,’Lisa Owens’,’Sugar Land’,’TX’,’United States’,’1/1/19 1:56′,’1/7/19 10:52′,29.61944,-95.63472,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 8:08′,’Chair’,1200,’Diners’,’Bryan Kerrene’,’New York’,’NY’,’United States’,’1/7/19 7:39′,’1/7/19 12:38′,40.71417,-74.00639,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/1/19 20:21′,’Chair’,1200,’Visa’,’Maxine Klein’,’Morton’,’IL’,’United States’,’10/24/18 6:48′,’1/7/19 20:49′,40.61278,-89.45917,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 0:42′,’Chair’,1200,’Visa’,’Buddy Dyer’,’Los Gatos’,’CA’,’United States’,’1/8/19 0:28′,’1/8/19 3:39′,37.22667,-121.97361,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 3:56′,’Chair’,1200,’Mastercard’,’Katherine Klein’,’New York’,’NY’,’United States’,’1/8/19 3:33′,’1/8/19 6:19′,40.71417,-74.00639,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 3:16′,’Bed’,7500,’Mastercard’,’Linda Smith’,’Miami’,’FL’,’United States’,’1/8/19 3:06′,’1/8/19 6:34′,25.77389,-80.19389,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/3/19 9:03′,’Chair’,1200,’Diners’,’Sheila Egg’,’Brooklyn’,’NY’,’United States’,’1/3/19 8:47′,’1/8/19 10:38′,40.65,-73.95,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/6/19 7:46′,’Chair’,1200,’Amex’,’Kelly Reilly’,’Reston’,’VA’,’United States’,’1/6/19 7:30′,’1/8/19 12:40′,38.96861,-77.34139,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 16:24′,’Chair’,1200,’Visa’,’Jennifer Price’,’Phoenix’,’AZ’,’United States’,’1/8/19 15:57′,’1/8/19 18:30′,33.44833,-112.07333,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/9/19 6:39′,’Chair’,1200,’Mastercard’,’Anneli Barker’,’houston’,’TX’,’United States’,’1/9/19 5:09′,’1/9/19 7:11′,29.76306,-95.36306,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/6/19 22:19′,’Bed’,7500,’Amex’,’Regis Ritz’,’Pittsfield’,’VT’,’United States’,’1/6/19 12:00′,’1/9/19 10:05′,43.77222,-72.81333,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/6/19 23:00′,’Couch’,3600,’Amex’,’Sophia Weimar’,’Pittsfield’,’VT’,’United States’,’1/6/19 12:00′,’1/9/19 10:05′,43.77222,-72.81333,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 7:44′,’Chair’,1200,’Mastercard’,’Marie Jenner’,’Ball Ground’,’GA’,’United States’,’1/7/19 5:35′,’1/9/19 10:52′,34.33806,-84.37667,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 15:12′,’Couch’,3600,’Visa’,’Anabela Taylor’,’Flossmoor’,’IL’,’United States’,’1/5/19 19:55′,’1/9/19 16:03′,41.54278,-87.68472,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 20:15′,’Chair’,1200,’Amex’,’Nicole Custer’,’Houston’,’TX’,’United States’,’1/7/19 17:17′,’1/9/19 20:02′,29.76306,-95.36306,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/3/19 10:11′,’Couch’,3600,’Visa’,’Christiane Hansen’,’Delray Beach’,’FL’,’United States’,’1/3/19 9:27′,’1/10/19 9:46′,26.46111,-80.07306,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/10/19 12:57′,’Couch’,3600,’Amex’,’Vanessa Kruth’,’Sandy Springs’,’GA’,’United States’,’2/7/07 20:16′,’1/10/19 14:09′,33.92417,-84.37861,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/10/19 12:05′,’Chair’,1200,’Visa’,’Anna Karina’,’Fort Lauderdale’,’FL’,’United States’,’7/1/18 12:53′,’1/10/19 16:33′,26.12194,-80.14361,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/10/19 14:56′,’Chair’,1200,’Visa’,’Angela Lansbury’,’Ankeny’,’IA’,’United States’,’1/8/19 3:06′,’1/10/19 19:41′,41.72972,-93.60556,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 10:01′,’Chair’,1200,’Visa’,’Darren Jones’,’Pittsboro’,’NC’,’United States’,’1/7/19 9:04′,’1/10/19 20:02′,35.72,-79.1775,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/1/19 1:26′,’Bed’,7500,’Mastercard’,’Nikki Sixx’,’New Rochelle’,’NY’,’United States’,’1/1/19 0:58′,’1/10/19 21:31′,40.91139,-73.78278,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/10/19 21:38′,’Chair’,1200,’Visa’,’Anushka Shetty’,’Maple Ridge District Municipality’,’BC’,’Canada’,’1/10/19 21:17′,’1/11/19 19:32′,49.25,-122.5,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 6:18′,’Chair’,1200,’Mastercard’,’Barney June’,’Beachwood’,’OH’,’United States’,’2/23/06 11:56′,’1/11/19 19:35′,41.46444,-81.50889,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/4/19 8:39′,’Couch’,3600,’Diners’,’Walter Baybars’,’Prince Albert’,’SK’,’Canada’,’1/3/19 17:17′,’1/11/19 21:05′,53.2,-105.75,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/12/19 3:25′,’Chair’,1200,’Mastercard’,’Chrissy Hines’,’W Lebanon’,’NH’,’United States’,’1/12/19 3:12′,’1/12/19 3:22′,43.64917,-72.31083,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 15:16′,’Bed’,7500,’Visa’,’Dottie Pang’,’Woodsboro’,’MD’,’United States’,’1/8/19 14:56′,’1/12/19 9:29′,39.53306,-77.315,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 20:22′,’Chair’,1200,’Visa’,’Gina Lindsey’,’Red Deer’,’AB’,’Canada’,’11/23/18 19:30′,’1/12/19 12:24′,52.2666667,-113.8,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 22:00′,’Chair’,1200,’Diners’,’Lynne Ford’,’Memphis’,’TN’,’United States’,’1/2/19 21:04′,’1/12/19 13:18′,35.14944,-90.04889,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 20:32′,’Chair’,1200,’Visa’,’Ju Kim’,’Calgary’,’AB’,’Canada’,’1/8/19 20:21′,’1/12/19 14:07′,51.0833333,-114.0833333,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 13:34′,’Chair’,1200,’Visa’,’Bruce Leider’,’Belleville’,’ON’,’Canada’,’1/6/19 14:38′,’1/12/19 18:31′,44.1666667,-77.3833333,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/11/19 13:08′,’Chair’,1200,’Visa’,’Rosa Markus’,’Cincinnati’,’OH’,’United States’,’1/11/19 12:38′,’1/12/19 18:44′,39.16194,-84.45694,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/12/19 19:04′,’Chair’,1200,’Visa’,’Lydia Franklin’,’Comox’,’BC’,’Canada’,’9/20/18 20:53′,’1/12/19 19:01′,49.6833333,-124.9333333,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/13/19 6:13′,’Chair’,1200,’Visa’,’Bobby Gitte’,’Staten Island’,’NY’,’United States’,’1/13/19 5:17′,’1/13/19 7:33′,40.63667,-74.15917,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/2/19 11:41′,’Chair’,1200,’Visa’,’Crystal Bale’,’Farmington’,’MI’,’United States’,’1/1/19 12:00′,’1/13/19 18:34′,42.46444,-83.37639,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/7/19 19:50′,’Chair’,1200,’Diners’,’Delphine Sanders’,’Santa Monica’,’CA’,’United States’,’1/3/19 12:04′,’1/13/19 20:17′,34.01944,-118.49028,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/1/19 20:28′,’Chair’,1200,’Visa’,’Nathalie Desai’,’Calgary’,’AB’,’Canada’,’1/1/19 20:11′,’1/13/19 21:11′,51.0833333,-114.0833333,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/3/19 15:22′,’Chair’,1200,’Mastercard’,’Lindi George’,’Vancouver’,’BC’,’Canada’,’2/20/18 22:45′,’1/13/19 23:02′,49.25,-123.1333333,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/12/19 3:03′,’Couch’,3600,’Mastercard’,’Valda Frank’,’Irvine’,’CA’,’United States’,’1/12/19 2:48′,’1/14/19 1:07′,33.66944,-117.82222,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/13/19 11:26′,’Chair’,1200,’Visa’,’Clare Voyant’,’Keller’,’VA’,’United States’,’1/13/19 11:15′,’1/14/19 2:39′,37.61917,-75.76417,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/14/19 4:54′,’Chair’,1200,’Mastercard’,’Zena Warrior’,’Honolulu’,’HI’,’United States’,’1/14/19 4:34′,’1/14/19 4:43′,21.30694,-157.85833,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/3/19 13:56′,’Chair’,1200,’Visa’,’Rennae Isard’,’Amelia Island’,’FL’,’United States’,’1/3/19 12:30′,’1/14/19 13:03′,30.66944,-81.46278,3);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/3/19 2:24′,’Bed’,7200,’Visa’,’Lisa Owens’,’Sugar Land’,’TX’,’United States’,’1/1/19 1:56′,’1/7/19 10:52′,29.61944,-95.63472,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/5/19 8:08′,’Bed’,7200,’Diners’,’Bryan Kerrene’,’New York’,’NY’,’United States’,’1/7/19 7:39′,’1/7/19 12:38′,40.71417,-74.00639,1);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/5/19 20:21′,’Bed’,7200,’Visa’,’Maxine Klein’,’Morton’,’IL’,’United States’,’10/24/18 6:48′,’1/7/19 20:49′,40.61278,-89.45917,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/8/19 0:45′,’Bed’,7200,’Visa’,’Buddy Dyer’,’Los Gatos’,’CA’,’United States’,’1/8/19 0:28′,’1/8/19 3:39′,37.22667,-121.97361,2);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/6/19 12:24′,’Couch’,5000,’Visa’,’Lisa Owens’,’Sugar Land’,’TX’,’United States’,’1/1/19 1:56′,’1/7/19 10:52′,29.61944,-95.63472,4);
INSERT INTO sales(transaction_date,product,price,payment_type,name,city,state,country,account_created,last_login,latitude,longitude,supplier) VALUES (‘1/9/19 9:24′,’Bed’,6000,’Visa’,’Lisa Owens’,’Sugar Land’,’TX’,’United States’,’1/1/19 1:56′,’1/7/19 10:52′,29.61944,-95.63472,4);
