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HAP 709 – Healthcare Databases

HAP 709 – Healthcare Databases. SQL Data Manipulation Language (DML) Updated Fall, 2009. SQL Components. SQL. DCL. DDL. DML. Data I/O. RDBMS Structure. DBA Activities. C reate Record. Create/Delete DBs. Create Users. R ead Record. Delete Users. Create/Delete Tables.

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HAP 709 – Healthcare Databases

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  1. HAP 709 – Healthcare Databases SQL Data Manipulation Language (DML) Updated Fall, 2009

  2. SQL Components SQL DCL DDL DML Data I/O RDBMS Structure DBA Activities Create Record Create/Delete DBs Create Users Read Record Delete Users Create/Delete Tables Grant privileges Update Record Alter Tables Implement AccessSecurity Delete Record

  3. SQL manipulates entire column of data No need to repeat the commands for each record

  4. SQL is non-procedural You do not need to tell the computer how to do the tasks. All you need to tell the computer is what you want to see and the computer will figure out how to produce the results you want to see

  5. Typical Commands • Details of commands are provided online. Here we review a select few commands • Key words are reserved for command specifications. These words cannot be used as names for fields or tables.

  6. Data Type Must be Specified • Number • Integer, Small integer, Big integer, Numeric data (with fraction), Decimal (with precision) • String • Character, Large character, National character • Boolean • Date/times • Date, Time with and without time zone, Timestamp with and without time zone • Intervals

  7. Data Manipulation Commands • Combined numeric values • Calculate intervals among dates/times • Process a series of Boolean statements • Concatenate strings together

  8. Logical Connectives • Allows you to build complex predicates out of simple ones • Set functions • Count, Max, Min, Sum, Avg, Stdev • Sub-queries

  9. Using SQL with Microsoft Access • Open database and select queries from objects • Select create query in design view • Add tables and close add tables button • Choose SQL view • Delete the select statement and enter commands you want • When finished save and enter a name for the query

  10. INSERT INTO Syntax INSERT INTO <myTable> VALUES (<Field1> <DataType>, <Field2> <DataType>,…);

  11. INSERT INTO Syntax INSERT INTO <myTable> VALUES (<Field1> <DataType>, <Field2> <DataType>,…); INSERT INTO PAT VALUES(983883,'JOHN','MARTINEZ');

  12. INSERT INTO in MS Access Note: In MS Access the INSERT INTO is called an Append Query

  13. UPDATE Statement (1) UPDATE <myTable> SET <Field1> = <Value1> WHERE {condition};

  14. UPDATE Statement (1) UPDATE <myTable> SET <Field1> = <Value1> WHERE {condition}; UPDATE PAT SET PAT_FNM = 'JOHNNY' WHERE PAT_ID = 983883;

  15. MS Access Example

  16. Updating Multiple Records(1) A new field needs to be populated after modification of the original table structure

  17. UPDATE Statement (2) UPDATE <myTable> {join} SET <Field1> = <Value1> WHERE {condition};

  18. UPDATE Statement (2) UPDATE <myTable> {join} SET <Field1> = <Value1> WHERE {condition}; UPDATE PAT INNER JOIN TEMP ON PAT.PAT_ID = TEMP.PAT_ID SET PAT.PAT_TITLE = TEMP.TITLE ;

  19. Multiple Updates in MS Access(1)

  20. Updating Multiple Records(2) The medical procedure cost table needs to be reflect a 12.5% increase

  21. UPDATE Statement (3) UPDATE <myTable> SET <Field1> = <Value1> WHERE {condition};

  22. UPDATE Statement (3) UPDATE <myTable> SET <Field1> = <Value1> WHERE {condition}; UPDATE MED_PROCEDURE SET COST = 1.125 * COST ;

  23. Multiple Updates in MS Access(2)

  24. Deleting a Record DELETE FROM <myTable> {condition};

  25. Deleting a Record DELETE FROM PAT WHERE PAT_ID = 983883; DELETE FROM <myTable> {condition};

  26. MS Access Example

  27. Reading the Data: the SELECT Statement SELECT {fields || *} FROM <myTable>{condition};

  28. Reading the Data: the SELECT Statement SELECT {fields || *} FROM <myTable>{condition}; SELECT PAT_LNM FROM PAT; SELECT * FROM PAT; SELECT MED_PROC_NM FROM MED_PROCEDURE WHERE COST > 20000;

  29. MS Access

  30. MS Access

  31. MS Access

  32. Joins Who is the primary physician for patient Mary Lindfors?

  33. Natural Join Who is/are the primary physician(s) for patient Mary Lindfors? SELECT PAT_FNM, PAT_LNM, CLNCIAN_NM FROM PAT, CLNCIAN WHERE PAT.PAT_ID = CLNCIAN.PAT_ID AND PAT_FNM = 'MARY' AND PAT_LNM = 'LINDFORS';

  34. MS Access

  35. Outer Joins: RIGHT JOIN SELECT PAT.PAT_FNM, PAT.PAT_LNM, CLNCIAN.CLNCIAN_NM FROM CLNCIAN RIGHT JOIN PAT ON CLNCIAN.PAT_ID = PAT.PAT_ID; Shows all the records from PAT and those records from CLNCIAN where the PAT_ID values are equal in both tables

  36. LEFT JOIN SELECT PAT.PAT_FNM, PAT.PAT_LNM, CLNCIAN.CLNCIAN_NM FROM CLNCIAN LEFT JOIN PAT ON CLNCIAN.PAT_ID = PAT.PAT_ID; Shows all the records from CLNCIAN and those records from PAT where the PAT_ID values are equal in both tables

  37. Union Operator • The tables must have the same number of columns • Corresponding columns must all have identical data types and lengths • Command syntax Select * From <First Table name> Union Select * From <Second Table name>;

  38. Union of Two Tables Recalled Medication in Use

  39. Union of Two Tables Recalled Medication in Use

  40. Union of Two Tables Recalled Medication in Use

  41. Intersect • Only rows of data that appear in both source tables are selected • Command Syntax Select * From <Table name> Intersect Corresponding (<Fieldname>, <Fieldname>, …) Select * From <Second Table name>;

  42. Except • Return all rows that appear in first table but not in the second table Select * From <Table name> Except Corresponding (<Fieldname>, <Fieldname>, …) Select * From <Second Table name>;

  43. Take Home Lessons It is possible to write your own SQL for data manipulation

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