Importance of Database Design in Commonwealth Swimming Games

The report would be used to present commonwealth games data in a modern database management system. The commonwealth database would be modeled using MYSQL so that is it quite easy to model and manage data. Data users would be able to query any aspect of data as required with minimal challenges and get results immediately. The compiled data would be only for swimming games as it is the section where Australia feels is more suited.

To prepare modern database, several measures should be factored. First, it is important to analyze the relationships that exist between entities. This helps database designer to determine mother table and child table. Database entity relationships are created through implementation of primary key on mother table and foreign key on child table. It is the same relationship that helps in data normalization by breaking data into atomic in nature. Data normalization is one of the aspects used by database designers’ ad developers to booster data integrity and consistency. Data consistency is of great importance in database design and management. Data inconsistency makes it difficult to use in business decision making. Since business decisions are made from business data analysis, inconsistency data makes it lose its integrity value. Without primary keys and foreign key implementation, it would be very difficult to normalize commonwealth database. Therefore, both primary key and foreign key are very essential in implementation of the subject database. Un-normalized data cannot be said to be atomic as required by principles of database design, ACID.

In this case, common wealth database design would follow all rules in order to implement a complete database. Event registration would be of very great importance as it would give room for other occasions to continue. Registration captures participant’s details to help in evaluation of member fitness and preparation to the games. Once participant has been registered, the swimmers category is further analyzed through their numbers so that it is easy to identity them. Importantly, swimmers are categorized depending on the type of swimming that they participate. To a larger extend, they are usually factored in terms of types of pools available. In this regard, it is easy to observe that, there are four different pools. Two of them have M 50M length and thy will serve as main pools to the swimming games. Interesting enough, the expected database would help in managing data recorded during the games. It would be possible to players who have not turned up, those who are available for completion, their preferences in the game, medical health records and tally of the results after completion.  

Designing the Commonwealth Swimming Games Database Using MYSQL

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— Database: `mthapa12…`

— — ——————————————————–

—

— Table structure for table `coaches`

— 

CREATE TABLE IF NOT EXISTS `coaches` (

  `Name` varchar(50) NOT NULL,

  `country` varchar(50) NOT NULL,

  `Mobile_c` int(11) NOT NULL,

  `Address` varchar(50) NOT NULL,

  `City` varchar(50) NOT NULL,

  `State` varchar(50) NOT NULL,

  `Post_code` varchar(50) NOT NULL,

  `certificate` int(11) NOT NULL,

  `certificate_date` date NOT NULL,

  `WWC_check` date NOT NULL,

  PRIMARY KEY (`Address`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8; 

—

— Dumping data for table `coaches`

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INSERT INTO `coaches` (`Name`, `country`, `Mobile_c`, `Address`, `City`, `State`, `Post_code`, `certificate`, `certificate_date`, `WWC_check`) VALUES

(‘Jonathan Singh’, ‘Australia’, 415, ‘177-1765 Nunc Av.’, ‘Rauco’, ‘TAS’, ‘7211’, 3, ‘2016-03-29’, ‘2017-03-07’),

(‘Nelly Newzie’, ‘New Zealand’, 415, ‘1875 Nec Road’, ‘Leamington’, ‘WA’, ‘6097’, 1, ‘2017-08-19’, ‘2017-03-28’),

(‘Susan Scotty’, ‘Scotland’, 415, ‘2037 Risus Road’, ‘Hulshout’, ‘WA’, ‘6599’, 2, ‘2016-10-24’, ‘2017-07-09’),

(‘Cool Cat’, ‘Canada’, 415, ‘2380 Ut St.’, ‘Hervey Bay’, ‘WA’, ‘6528’, 4, ‘2015-09-17’, ‘2016-10-30’),

(‘Innes Indy’, ‘India’, 415, ‘241-8201 Eu Street’, ‘Gjoa Haven’, ‘ NSW ‘, ‘2796’, 4, ‘2016-02-25’, ‘2016-08-18’),

(‘Island Man’, ‘Isle of Man’, 415, ‘245-5949 Vehicula St.’, ‘Sant”Angelo a Fasanella’, ‘ NSW ‘, ‘2652’, 5, ‘2017-04-09’, ‘2015-01-09’),

(‘Jammin Juice’, ‘Jamaica’, 415, ‘254-7049 Pede. Street’, ‘Chaitén’, ‘ NSW ‘, ‘2994’, 5, ‘2015-05-10’, ‘2015-07-13’),

(‘Keith Kenyan’, ‘Kenya’, 415, ‘263-5742 Enim. St.’, ‘Lake Cowichan’, ‘WA’, ‘6317’, 5, ‘2016-05-09’, ‘2016-08-23’),

(‘Noddy North’, ‘Northern Ireland’, 415, ‘271-5702 Consequat, Rd.’, ‘Sulzbach’, ‘ NSW ‘, ‘2035’, 3, ‘2016-03-08’, ‘2017-05-05’),

(‘Peter Parker’, ‘Pakistan’, 415, ‘2790 Facilisis Rd.’, ‘Francavilla in Sinni’, ‘VIC’, ‘3759’, 2, ‘2016-04-13’, ‘2016-02-06’),

(‘Rowie Roundtree’, ‘Rwanda’, 415, ‘292-1554 Tempor Road’, ‘Gorzów Wielkopolski’, ‘TAS’, ‘7663’, 2, ‘2016-02-26’, ‘2017-02-22’),

(‘Saint Helen’, ‘Saint Helena’, 415, ‘295 A Rd.’, ‘Auburn’, ‘SA’, ‘5672’, 1, ‘2015-09-25’, ‘2015-01-02’),

(‘Jennifer Brown’, ‘Australia’, 411, ‘3/73 Mauris Avenue’, ‘Evans Head’, ‘ NSW ‘, ‘2473’, 4, ‘2016-07-20’, ‘2015-07-25’),

(‘Leonie Sera’, ‘Sierra Leone’, 415, ‘3025 Luctus Road’, ‘Andernach’, ‘TAS’, ‘7417’, 3, ‘2015-08-22’, ‘2016-09-23’),

(‘Steven Singh’, ‘Singapore’, 415, ‘3347 Euismod Ave’, ‘Quibby City’, ‘ NSW ‘, ‘2242’, 3, ‘2015-10-15’, ‘2016-07-27’),

(‘Suth Stevens’, ‘South Africa’, 415, ‘345-3924 Fringilla Av.’, ‘Dufftown’, ‘ NSW ‘, ‘2451’, 4, ‘2016-01-18’, ‘2016-06-13’),

(‘Tommy Tanny’, ‘Tanzania’, 415, ‘3459 Orci Avenue’, ‘Konin’, ‘SA’, ‘5199’, 5, ‘2015-11-12’, ‘2015-09-29’),

(‘Therese Tong’, ‘Tonga’, 415, ‘3672 Augue, Street’, ‘Uberaba’, ‘ NSW ‘, ‘2826’, 2, ‘2016-11-13’, ‘2016-03-31’),

Event Registration and Participant Analysis

(‘Tommy Taboggin’, ‘Trinidad and Tobago’, 415, ‘431-2939 Lorem, Rd.’, ‘Pune’, ‘ NSW ‘, ‘2234’, 4, ‘2016-12-30’, ‘2016-06-30’),

(‘Boogy Bermy’, ‘Bermuda’, 415, ‘454-180 Ridiculus Avenue’, ‘Los Angeles’, ‘TAS’, ‘7031’, 3, ‘2016-10-18’, ‘2017-05-11’),

(‘Benjamin Yang’, ‘Australia’, 415, ‘4816 Mauris St.’, ‘Beigem’, ‘WA’, ‘6906’, 3, ‘2016-10-24’, ‘2015-07-31’),

(‘Bill Brown’, ‘Britain’, 415, ‘485-4275 Donec Rd.’, ‘Rae Lakes’, ‘TAS’, ‘7479’, 4, ‘2016-08-03’, ‘2016-07-08’); 

— ——————————————————– 

—

— Table structure for table `Contact`– 

CREATE TABLE IF NOT EXISTS `Contact` (

  `Name` varchar(50) NOT NULL,

  `State_c` varchar(50) NOT NULL,

  `Mobile_c` int(10) NOT NULL,

  `Address` varchar(50) NOT NULL,

  `City` varchar(50) NOT NULL,

  `State` varchar(50) NOT NULL,

  `Post_code` int(11) NOT NULL,

  `Contact_type` varchar(50) NOT NULL,

  PRIMARY KEY (`Mobile_c`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8; 

—

— Dumping data for table `Contact`

— 

INSERT INTO `Contact` (`Name`, `State_c`, `Mobile_c`, `Address`, `City`, `State`, `Post_code`, `Contact_type`) VALUES

(‘Jenny Myles’, ‘Australia’, 415, ‘P.O. Box 408, 798 Ornare, Av.’, ‘Roveredo in Piano’, ‘VIC’, 3670, ‘Team Manager’); 

— ——————————————————–

—

— Table structure for table `Countries`

— 

CREATE TABLE IF NOT EXISTS `Countries` (

  `State` varchar(50) NOT NULL,

  `Main_contact` varchar(50) NOT NULL,

  PRIMARY KEY (`State`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8; 

—

— Dumping data for table `Countries`

—

 INSERT INTO `Countries` (`State`, `Main_contact`) VALUES

(‘ Britain’, ”),

(‘ Anguilla’, ”),

(‘ Antigua and Barbuda’, ”),

(‘ Australia (host nation)’, ‘Jenny Myles’),

(‘ Bahamas’, ”),

(‘ Bangladesh’, ”),

(‘ Barbados’, ”),

(‘ Belize’, ”),

(‘ Bermuda’, ”),

(‘ Botswana’, ”),

(‘ British Virgin Islands’, ”),

(‘ Brunei’, ”),

(‘ Cameroon’, ”),

(‘ Canada’, ”),

(‘ Cayman Islands’, ”),

(‘ Cook Islands’, ”),

(‘ Cyprus’, ”),

(‘ Dominica’, ”),

(‘ Falkland Islands’, ”),

(‘ Fiji’, ”),

(‘ Ghana’, ”),

(‘ Gibraltar’, ”),

(‘ Grenada’, ”),

(‘ Guernsey’, ”),

(‘ Guyana’, ”),

(‘ India’, ”),

(‘ Isle of Man’, ”),

(‘ Jamaica’, ”),

(‘ Jersey’, ”),

(‘ Kenya’, ”),

(‘ Kiribati’, ”),

(‘ Lesotho’, ”),

(‘ Malawi’, ”),

(‘ Malaysia’, ”),

(‘ Malta’, ”),

(‘ Mauritius’, ”),

(‘ Montserrat’, ”),

(‘ Mozambique’, ”),

(‘ Namibia’, ”),

(‘ Nauru’, ”),

(‘ New Zealand’, ”),

(‘ Nigeria’, ”),

(‘ Niue’, ”),

(‘ Norfolk Island’, ”),

(‘ Northern Ireland’, ”),

(‘ Pakistan’, ”),

(‘ Papua New Guinea’, ”),

(‘ Rwanda’, ”),

(‘ Saint Helena’, ”),

(‘ Saint Kitts and Nevis’, ”),

(‘ Saint Lucia’, ”),

(‘ Saint Vincent and the Grenadines’, ”),

(‘ Samoa’, ”),

(‘ Scotland’, ”),

(‘ Seychelles’, ”),

(‘ Sierra Leone’, ”),

(‘ Singapore’, ”),

(‘ Solomon Islands’, ”),

(‘ South Africa’, ”),

(‘ Sri Lanka’, ”),

(‘ Swaziland’, ”),

(‘ Tanzania’, ”),

(‘ Tonga’, ”),

(‘ Trinidad and Tobago’, ”),

(‘ Turks and Caicos Islands’, ”),

(‘ Tuvalu’, ”),

(‘ Uganda’, ”),

(‘ Vanuatu’, ”),

(‘ Wales’, ”),

(‘ Zambia’, ”); 

— ——————————————————–

 —

— Table structure for table `Event`

— 

CREATE TABLE IF NOT EXISTS `Event` (

  `Event` varchar(50) NOT NULL,

  `Qualify_Time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP

Pool Categorization and Management During the Games

) ENGINE=InnoDB DEFAULT CHARSET=utf8; 

—

— Dumping data for table `Event`

— 

INSERT INTO `Event` (`Event`, `Qualify_Time`) VALUES

(’50m Backstroke – Men’, ‘0000-00-00 00:00:00’),

(’50m Backstroke – Women’, ‘0000-00-00 00:00:00’),

(’50m Breaststroke – Men’, ‘0000-00-00 00:00:00’),

(’50m Breaststroke – Women’, ‘0000-00-00 00:00:00’),

(’50m Butterfly – Men’, ‘0000-00-00 00:00:00’),

(’50m Butterfly – Women’, ‘0000-00-00 00:00:00’); 

— ——————————————————– 

—

— Table structure for table `Event_registration`

— 

CREATE TABLE IF NOT EXISTS `Event_registration` (

  `Event_Name` varchar(50) NOT NULL,

  `Swimmer_No` int(11) NOT NULL,

  `Swimmer_Name` int(11) NOT NULL,

  `Qualify_Time` time NOT NULL,

  `Qualify_Date` date NOT NULL,

  `Qualify_competition` varchar(50) NOT NULL,

  PRIMARY KEY (`Swimmer_No`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 — ——————————————————–

 —

— Table structure for table `Medical`

—

 CREATE TABLE IF NOT EXISTS `Medical` (

  `Name` varchar(50) NOT NULL,

  `country` varchar(50) NOT NULL,

  `Mobile_c` int(10) NOT NULL,

  `Address` varchar(50) NOT NULL,

  `City` varchar(50) NOT NULL,

  `State` varchar(50) NOT NULL,

  `Post_code` int(11) NOT NULL,

  `Qualification` varchar(50) NOT NULL,

  `Q_year` year(4) NOT NULL,

  `specification` varchar(50) NOT NULL,

  PRIMARY KEY (`Name`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

—

— Dumping data for table `Medical`

— 

INSERT INTO `Medical` (`Name`, `country`, `Mobile_c`, `Address`, `City`, `State`, `Post_code`, `Qualification`, `Q_year`, `specification`) VALUES

(‘Alan Ozzie’, ‘Australia’, 411, ‘P.O. Box 227, 1682 Cum St.’, ‘Landeck’, ‘NSW’, 2666, ‘MD’, 2001, ”),

(‘Bobby Brown’, ‘Britain’, 414, ‘P.O. Box 255, 3251 Diam Av.’, ‘Großpetersdorf’, ‘NSW’, 2444, ‘MD’, 1978, ”),

(‘Kiona Sykes’, ‘Australia’, 412, ‘P.O. Box 206, 6847 A, Rd.’, ‘Tione di Trento’, ‘WA’, 6915, ‘MD’, 1996, ‘Orthopaedics’),

(‘Noddy Zimmer’, ‘New Zealand’, 421, ‘P.O. Box 347, 6201 Sed Street’, ‘Candela’, ‘VIC’, 3226, ‘M.Med’, 2003, ”),

(‘Sally Stuart’, ‘Scotland’, 411, ‘P.O. Box 273, 7892 Aliquam Ave’, ‘Momignies’, ‘TAS’, 7766, ‘MBBS’, 1990, ‘Surgery’); 

— ——————————————————– 

—

— Table structure for table `pools`

—

CREATE TABLE IF NOT EXISTS `pools` (

  `Pool number` int(11) NOT NULL,

  `pool name` varchar(50) NOT NULL,

  `Lane count` int(11) NOT NULL,

  `Length(M)` int(11) NOT NULL,

  PRIMARY KEY (`Pool number`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8; 

—

— Dumping data for table `pools`

—

INSERT INTO `pools` (`Pool number`, `pool name`, `Lane count`, `Length(M)`) VALUES

(1, ‘Competition Pool’, 10, 50),

(2, ‘Training Pool’, 8, 50),

(3, ‘Program pool’, 7, 25),

(4, ‘Diving Pool’, 0, 33);

 — ——————————————————–

 —

— Table structure for table `Races`

— 

CREATE TABLE IF NOT EXISTS `Races` (

  `Event_name` varchar(50) NOT NULL,

  `Race_name` varchar(50) NOT NULL,

  `Day` int(2) NOT NULL,

  `Start_time` time NOT NULL,

  `Location` varchar(50) NOT NULL,

  PRIMARY KEY (`Start_time`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8; 

—

— Dumping data for table `Races`

—

 INSERT INTO `Races` (`Event_name`, `Race_name`, `Day`, `Start_time`, `Location`) VALUES

(’50m Freestyle – Women’, ‘Heat 1′, 1, ’10:15:00’, ‘Training Pool’),

(’50m Freestyle – Women’, ‘Heat 2′, 1, ’10:20:00’, ‘Training Pool’),

(’50m Freestyle – Women’, ‘Heat 3′, 1, ’10:25:00’, ‘Training Pool’),

(’50m Freestyle – Women’, ‘Heat 4′, 1, ’10:30:00’, ‘Training Pool’),

(’50m Freestyle – Women’, ‘Semi-Final 1′, 1, ’10:45:00’, ‘Competition Pool’),

(’50m Freestyle – Women’, ‘Semi-Final 2′, 1, ’10:50:00’, ‘Competition Pool’),

(’50m Freestyle – Women’, ‘Final’, 1, ’10:55:00′, ‘Competition Pool’),

(’50m Freestyle – Men’, ‘Heat 1′, 1, ’11:15:00’, ‘Training Pool’),

(’50m Freestyle – Men’, ‘Heat 2′, 1, ’11:20:00’, ‘Training Pool’),

(’50m Freestyle – Men’, ‘Heat 3′, 1, ’11:25:00’, ‘Training Pool’),

(’50m Freestyle – Men’, ‘Heat 4′, 1, ’11:30:00’, ‘Training Pool’),

(’50m Freestyle – Men’, ‘Semi-Final 1′, 1, ’11:45:00’, ‘Competition Pool’),

(’50m Freestyle – Men’, ‘Semi-Final 2′, 1, ’11:50:00’, ‘Competition Pool’),

(’50m Freestyle – Men’, ‘Final’, 1, ’11:55:00′, ‘Competition Pool’); 

— ——————————————————–

—

— Table structure for table `Race_swimmer`

—

 CREATE TABLE IF NOT EXISTS `Race_swimmer` (

  `Event_name` varchar(50) NOT NULL,

  `Race_name` varchar(50) NOT NULL,

  `swimmerNo` int(11) NOT NULL,

  `Swimmer_name` varchar(50) NOT NULL,

  `lane` int(11) NOT NULL,

  `Record_Time` float NOT NULL,

  `Place` int(11) NOT NULL,

  PRIMARY KEY (`swimmerNo`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

—

— Dumping data for table `Race_swimmer`

— 

INSERT INTO `Race_swimmer` (`Event_name`, `Race_name`, `swimmerNo`, `Swimmer_name`, `lane`, `Record_Time`, `Place`) VALUES

(’50m Freestyle – Women’, ‘Heat 1’, 12, ‘Ella Cook’, 5, 23, 1),

(’50m Freestyle – Women’, ‘Heat 1’, 17, ‘Hannah Roy’, 3, 24, 4),

(’50m Freestyle – Women’, ‘Heat 1’, 23, ‘Jenny Myles’, 2, 23.55, 2),

(’50m Freestyle – Women’, ‘Heat 1’, 34, ‘Rebekah Riley’, 1, 23.96, 3),

(’50m Freestyle – Men’, ‘Heat 1’, 41, ‘Sue Simpson’, 5, 0, 0),

(’50m Freestyle – Men’, ‘Heat 1’, 42, ‘Tony Ratcliffe’, 6, 0, 0),

(’50m Freestyle – Women’, ‘Heat 1’, 43, ‘Zorita Kim’, 4, 24.01, 0),

(’50m Freestyle – Men’, ‘Heat 1’, 44, ‘Barry White’, 7, 0, 0),

(’50m Freestyle – Men’, ‘Heat 1’, 45, ‘Bob Brittany’, 8, -0, 0); 

— ——————————————————–

 —- Table structure for table `Swimmers`

— 

CREATE TABLE IF NOT EXISTS `Swimmers` (

  `state` varchar(50) NOT NULL,

  `gender` varchar(50) NOT NULL,

  `Mobile` int(10) NOT NULL,

  `Address` varchar(50) NOT NULL,

  `City` varchar(50) NOT NULL,

  `P_country` varchar(50) NOT NULL,

  `postcode` int(10) NOT NULL,

  `coach` varchar(50) NOT NULL,

  `Date_birth` date NOT NULL

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 —

— Dumping data for table `Swimmers`– 

INSERT INTO `Swimmers` (`state`, `gender`, `Mobile`, `Address`, `City`, `P_country`, `postcode`, `coach`, `Date_birth`) VALUES

(‘NT’, ‘Female’, 415, ‘673-4905 Donec Road’, ‘Spresiano’, ‘New Zealand’, 1028, ‘Nelly Newzie’, ‘0000-00-00’),

(‘NT’, ‘Female’, 415, ‘673-4905 Donec Road’, ‘Spresiano’, ‘New Zealand’, 1028, ‘Nelly Newzie’, ‘0000-00-00’),

(‘NT’, ‘Female’, 415, ‘831 Non Avenue’, ‘Kortrijk’, ‘India’, 1120, ‘Innes Indy’, ‘1995-03-19’),

(‘NT’, ‘Female’, 415, ‘6176 Nec Rd.’, ‘Bicester’, ‘Australia’, 1639, ‘Benjamin Yang’, ‘1993-08-18’),

(‘NT’, ‘Female’, 415, ‘5515 Rutrum Street’, ‘Lublin’, ‘Britain’, 1765, ‘Bill Brown’, ‘1996-07-25’),

(‘NSW’, ‘Female’, 423, ’12 Potter Avenue’, ‘Pottsville’, ‘Australia’, 2433, ‘Benjamin Yang’, ‘1999-02-09’),

(‘NSW’, ‘Female’, 415, ‘8770 Pharetra Road’, ‘Oranienburg’, ‘South Africa’, 2956, ‘Suth Stevens’, ‘2000-09-17’),

(‘VIC’, ‘Female’, 415, ‘613-3725 Natoque St.’, ‘Red Deer’, ‘Canada’, 3564, ‘Cool Cat’, ‘1991-01-24’),

(‘VIC’, ‘Female’, 415, ‘9120 Ut Ave’, ‘Mühlheim am Main’, ‘Kenya’, 3936, ‘Keith Kenyan’, ‘1995-02-25’),

(‘QLD’, ‘Female’, 415, ‘7096 Malesuada Rd.’, ‘Doetinchem’, ‘Trinidad and Tobago’, 4053, ‘Tommy Taboggin’, ‘1992-05-15’),

(‘QLD’, ‘Female’, 415, ‘908-8505 Facilisis Avenue’, ‘Boston’, ‘Jamaica’, 4404, ‘Jammin Juice’, ‘1993-02-09’),

(‘QLD’, ‘Female’, 415, ‘528-4851 Ut, Rd.’, ‘Goulburn’, ‘Tonga’, 4406, ‘Therese Tong’, ‘2002-03-05’),

(‘SA’, ‘Female’, 415, ‘7531 Hymenaeos. Rd.’, ‘Rankweil’, ‘Australia’, 5121, ‘Jonathan Singh’, ‘1991-05-31’),

(‘SA’, ‘Female’, 415, ‘7566 At, Av.’, ‘Alto Hospicio’, ‘Australia’, 5971, ‘Jennifer Brown’, ‘1997-04-09’),

(‘WA’, ‘Female’, 415, ‘585-4400 Libero. Rd.’, ‘Curaco de Vélez’, ‘Canada’, 6699, ‘Cool Cat’, ‘1997-05-14’),

(‘TAS’, ‘Female’, 415, ‘4892 Commodo Road’, ‘Stendal’, ‘Britain’, 7512, ‘Bill Brown’, ‘1995-03-11’); 

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1. SQL queries
2. SELECT swimmers.Name,swimmer.swimmer#, swimmer.Mobile,coaches.Name,Medical.Name, contact.Name from swimmer,coaches,Medical where swimmer.country = kenya,coaches.country=parkistan and Medical.Mobile = 0412 555 666;
3. SELECT count (country,Name) from Swimmers order by country DESC;

iii. SELECT country, Swimmer.swimmer_name,swimmer.Address,swimmer.Mobile_c,Race_swimmers.Event_Name, Event.MQualify_Time,Race_swimmer.Qualify_Time, Race_swimmers.Redorded_Time from Swimmers,Event,Race_Swimmers Where Qualify_Time=Mqualify_Time;

1. SELECT Name,Address, Mobile_c, country, Specification FROM `Medical` order by Name; 

1. SELECT Event_Name, Race_Name, Start_Time, Location FROM `Races` WHERE Event_Name=’50m Freestyle – Women’Order by Race_name; 

1. SELECT Event_name,Swimmer_name, Record_Time FROM `Race_swimmer` WHERE Place=1; 

SELECT Event_name,Swimmer_name, Record_Time FROM `Race_swimmer` WHERE Place=2;

SELECT Event_name,Swimmer_name, Record_Time FROM `Race_swimmer` WHERE Place=3; 

Vii.  SELECT swimmer_name, Record_Time, place FROM `Race_swimmer` WHERE Place=3 order by event_name; 

viii. select swimmerNo,place from Race_swimmer

Inner Join

country on swimmer.Name;

1. select swimmerNo,country,Mobile_c,Qualify_level,place from Race_swimmer

Inner Join

Medical on Qualifications, specification;