collected in a spreadsheet (an extract from the spreadsheet is shown below). The data has been normalised to first normal form already – underlined column names indicate composite primary key columns. Skill Hairdresser Skill Level Final Name Surname SkilI ID Skill Name Level ID Description Mark ID Joe Mahlasela 1 Styling 1 Basic 75 1 Joe Mahlasela 2 Shampooing 1 Basic 67 1 Joe Mahlasela 3 Cutting 2 Intermediate 98 1 Joe Mahlasela 4 Colouring 2 Intermediate 2 Martha Lebusa 1 Styling 1 Basic 76 2 Martha Lebusa 2 Shampooing 1 Basic 51 2 Martha Lebusa 3 Cutting 2 Intermediate 54 Normalise the above data to third normal form (3NF). Show all steps as well as the final answer in the form of dependency diagrams. HNN
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- Imagine a spreadsheet with the following rows: NAME AGE WINS Samantha 15 8 Carrie 22 5 Charlotte 38 3 Miranda 19 9 The first row is a header. By default, sorting on Name, what would the rows look like? Which non-header row would be first if you sorted on WINS using Excel’s default sort option?Given the following query SELECT StudID, CourseTitle, CreditsFROM Enrollment, CourseWHERE Enrollment.CourseTitle = Course.CourseTitle ANDEnrollment.Decision = TRUE and Course.Credits > 4which of the following indexes could NOT be useful inspeeding-up the query? a) tree-based index on Enrollment.CourseTitleb) hash-based index on Enrollment.Decisionc) hash-based index on Course.CourseTitled) hash-based index on Course.Credits Can someone explain me step by step which is the correct answer and why,please?/* Created with SQL Script Builder v.1.5 */ /* Type of SQL : SQL Server */ CREATE TABLE EMPLOYEE ( EMP_CODE int, EMP_TITLE varchar(4), EMP_LNAME varchar(15), EMP_FNAME varchar(15), EMP_INITIAL varchar(1), EMP_DOB datetime, JOB_CODE varchar(5), STORE_CODE int ); INSERT INTO EMPLOYEE VALUES('1','Mr.','Williamson','John','W','5/21/1964','SEC','3'); INSERT INTO EMPLOYEE VALUES('2','Ms.','Ratula','Nancy','','2/9/1969','MGR','2'); INSERT INTO EMPLOYEE VALUES('3','Ms.','Greenboro','Lottie','R','10/2/1961','GEN','4'); INSERT INTO EMPLOYEE VALUES('4','Mrs.','Rumpersfro','Jennie','S','6/1/1971','GEN','5'); INSERT INTO EMPLOYEE VALUES('5','Mr.','Smith','Robert','L','11/23/1959','GEN','3'); INSERT INTO EMPLOYEE VALUES('6','Mr.','Renselaer','Cary','A','12/25/1965','GEN','1'); INSERT INTO EMPLOYEE VALUES('7','Mr.','Ogallo','Roberto','S','7/31/1962','MGR','3'); INSERT INTO EMPLOYEE VALUES('8','Ms.','Johnsson','Elizabeth','I','9/10/1968','SEC','1'); INSERT INTO EMPLOYEE…
- /* Created with SQL Script Builder v.1.5 */ /* Type of SQL : SQL Server */ CREATE TABLE EMPLOYEE ( EMP_CODE int, EMP_TITLE varchar(4), EMP_LNAME varchar(15), EMP_FNAME varchar(15), EMP_INITIAL varchar(1), EMP_DOB datetime, JOB_CODE varchar(5), STORE_CODE int ); INSERT INTO EMPLOYEE VALUES('1','Mr.','Williamson','John','W','5/21/1964','SEC','3'); INSERT INTO EMPLOYEE VALUES('2','Ms.','Ratula','Nancy','','2/9/1969','MGR','2'); INSERT INTO EMPLOYEE VALUES('3','Ms.','Greenboro','Lottie','R','10/2/1961','GEN','4'); INSERT INTO EMPLOYEE VALUES('4','Mrs.','Rumpersfro','Jennie','S','6/1/1971','GEN','5'); INSERT INTO EMPLOYEE VALUES('5','Mr.','Smith','Robert','L','11/23/1959','GEN','3'); INSERT INTO EMPLOYEE VALUES('6','Mr.','Renselaer','Cary','A','12/25/1965','GEN','1'); INSERT INTO EMPLOYEE VALUES('7','Mr.','Ogallo','Roberto','S','7/31/1962','MGR','3'); INSERT INTO EMPLOYEE VALUES('8','Ms.','Johnsson','Elizabeth','I','9/10/1968','SEC','1'); INSERT INTO EMPLOYEE…/* Created with SQL Script Builder v.1.5 */ /* Type of SQL : SQL Server */ CREATE TABLE EMPLOYEE ( EMP_CODE int, EMP_TITLE varchar(4), EMP_LNAME varchar(15), EMP_FNAME varchar(15), EMP_INITIAL varchar(1), EMP_DOB datetime, JOB_CODE varchar(5), STORE_CODE int ); INSERT INTO EMPLOYEE VALUES('1','Mr.','Williamson','John','W','5/21/1964','SEC','3'); INSERT INTO EMPLOYEE VALUES('2','Ms.','Ratula','Nancy','','2/9/1969','MGR','2'); INSERT INTO EMPLOYEE VALUES('3','Ms.','Greenboro','Lottie','R','10/2/1961','GEN','4'); INSERT INTO EMPLOYEE VALUES('4','Mrs.','Rumpersfro','Jennie','S','6/1/1971','GEN','5'); INSERT INTO EMPLOYEE VALUES('5','Mr.','Smith','Robert','L','11/23/1959','GEN','3'); INSERT INTO EMPLOYEE VALUES('6','Mr.','Renselaer','Cary','A','12/25/1965','GEN','1'); INSERT INTO EMPLOYEE VALUES('7','Mr.','Ogallo','Roberto','S','7/31/1962','MGR','3'); INSERT INTO EMPLOYEE VALUES('8','Ms.','Johnsson','Elizabeth','I','9/10/1968','SEC','1'); INSERT INTO EMPLOYEE…Given the business rule "An employee may have many degrees." Suppose that an employee has the following degrees. BA, BS, MBA, etc. These degrees could be stored in a single string as a multivalued attribute name EMP_DEGREE in an EMPLOYEE table such as the one shown below: EMP_NUM EMP_LNAME EMP_DEGREE 123 Carter BA, BS, MBA 124 Smith BBA, MBA 125 Jones AS 126 Doe BS, MS, PhD. This design is flawed, so correct it by creating additional table(s) and attributes(s) and show the relationships between them. Show all the data above in your table(s). Add additional data if new attributes were added. Show primary and foreign keys in your table(s).
- The following statement tells the decomposition of the people survived a.k.a column Survived as of 0 (not survived) or 1 (survived). Create a similar statement using groupby function to further breakdown by Sex. In other words, add additional sex dimension. The desired output should be similar to the following: Sex Survided female 0 81 1 233 male 0 468 1 109Name: Survived, dtype: int64 In [16]:The first step in finding an association between gender and handedness from among the students in the accompanying table is to create a two-way table with these two variables. Make a two-way table with the labels Male and Female across the top and the labels Right and Left on the side, and then answer questions (a) through (f) using it. LOADING... Click the icon to view the data table. a. Report how many students are in each of the four cells of the table by writing these values in your table. Refer to the spreadsheet given below to begin tallying. For each cell, make a tally mark using the capital letter I for each person who has both of the characteristics belonging to that cell. Type a 0 if there are no students with the given characteristics. The genders have been recorded without coding to make the tallying process a little easier. Put a check mark to the right of the table so you know how far you have gotten. The first four tally marks are given. Check to…Passenger (pid, pbithday, pcity)Station (sid, sname, sxcoord, sycoord)CheckIn (pid, departure_sid, arrive_sid, departure_date, arrive_date)departure_sid reference sid in Stationarrive_sid reference sid in Stationpid references pid in Passenger there are 400 million Passenger, 500 stations, and 20 billion checkIn stored in the schema. For simplicity, assume that every attribute is of size 8 bytes, and the size of each tuple is thus 8*x bytes for a table with x attributes, and that the size of a table is simply the size of a tuple multiplied by the number of tuples (i.e., 100% occupancy and no gaps or space for block metadata). Now consider the following queries: SELECT P.pidFROM Passenger p, CheckIn C, Station SWHERE P.pid = C.pidand C.departure_sid = S.sidand S.sname = "LA"and year(P.pbithday) = 2000and date(C.departure_date) = "2015-12-12" question:1. first join P with C, and then join result with S2. first join S with C, and then join result with PWhich way would be faster for this…
- Create the following indices, giving them an appropriate name in your spreadsheet (make sure to use the reverse-coded variable where relevant): Belief that climate change is a real phenomenon: Take the mean of scepticism_2, scepticism_6, and scepticism_7. Preferences for government intervention to solve problems in society: Take the mean of cog_1, cog_2, cog_3, cog_4, cog_5, and cog_6. Feeling of personal responsibility to act pro-environmentally: Take the mean of PN_1, PN_2, PN_3, PN_4, PN_6, and PN_7. When creating indices, we may be interested to see if each item used in the index measures the same underlying variable of interest (known as reliability or consistency). There are two common ways to assess reliability: either look at the correlation between items in the index, or use a summary measure called Cronbach’s alphaCronbach’s alpha A measure used to assess the extent to which a set of items is a reliable or consistent measure of a concept. This measure ranges from 0–1,…A table called "game1" contains three columns and twenty rows, but "game2" has the same column as game1 (ie 3) and fifteen rows. Both tables have 5 rows in common. What is the degree and cardinality of the resulting table if we take union?_&plase helo with Course: Database *(SQL)* Please excute the given SQL script (https://drive.google.com/file/d/1zxe_aOhERjVCL54_zbgSLkFTRHYQhOPW/view?usp=sharing) for accessing the data. The data is described in the following relation schemas: Airport (airportID, name, city) Passenger (ticketNo, name, nationality, flightNo, seatNo)FK: flightNo references Flight (flightNo)FK: seatNo references Seat (seatNo) Flight (flightNo, flightCompany, departAirport, arrivalAirport)FK: departAirport references Airport (airportID)FK: arrivalAirport references Airport (airportID) Seat (seatNo, flightNo, class)FK: flightNo references Flight (flightNo) #Construct the SQL statements based on following transactions:1. Retrieve all rows in Airport table for all the airports in London city.2. Retrieve all British and German passengers.3. Retrieve all names of all the passengers..