JOINING DATA TO FIND THE DEBTORS USING MICROSOFT ACCESS

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1 JOINING DATA TO FIND THE DEBTORS USING MICROSOFT ACCESS Jim Mosley (Updated for Access 2010) Skills Summary: In this lesson, you will review basic query steps, perform multiple grouping of data, make a new table from a query, review calculated fields, join tables, look for dirty data and look for trends between two different tables. Illinois has been criticized for being one of the worst states in terms of collecting child support. You have decided to use a computer to find out just how bad. First, you get an electronic copy of parents in Illinois who are delinquent in their child support. Open the file called ILDEBTOR.mdb, and double-click on the table called ORDERS to see the table. Record layout ORDERS: Field Name Type Description NAME Text Name of debtor, in the form LNAME SUFFIX FNAME MNAME STREET Text Street address CITY Text City of residence at the time of the order STATE Text State of residence at the time of the order ZIP Text Zip of residence at the time of the order DOB Date/Time Date of Birth ORD_DAT Date/Time Date of the order DEBT Number Amount of the debt NUM_KIDS Number Number of children it applies to Note that each record refers to a judicial order, not a person. It s quite possible that one parent has been slapped with more than one judgment. You should also note the format of the name, along with any useful fields for identifying people. That table looks like this: Let s query, or ask questions, of the table. Remember the steps to starting an Access query: in the Create tab click on Query Design, add your table(s) and switch to SQL View Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 1

We want the list of child-support delinquents. Let s review the query options: SELECT Fields. Use the SELECT statement to choose the fields you want to see.

2 We want the list of child-support delinquents. Let s review the query options: SELECT Fields. Use the SELECT statement to choose the fields you want to see. You can select all fields by using only the asterisk. FROM table. Put in the table or tables you want to query. WHERE Criteria. You set criteria for fields, filtering your results. GROUP BY. Use this to break down data by a value of a field. Remember, it s not for detail. ORDERing or Sorting. Use this to rank values. You can sort on multiple fields, and sort ascending (lowest to highest) or descending (highest to lowest). Running Queries. Click on the exclamation point (in the Design tab). Let s query the database to count how many times each name appears in the table. We also want to rank the names from highest to lowest. First, let s think about the query before we build it. We want to break down the data by name. That tells us we want a Group By statement on name. We want to count the names, so we would use the Count function. And we want to rank the data, so we want a sort, or order statement on the count. Here s what that query should look like: SELECT name, count(*) GROUP BY name ORDER BY 2 desc Here is what our results should look like: In this view, Michael Williams had 12 orders against him, out of a database of 3,911 orders. Problem is, there could be many Michael Williams in Illinois who owe delinquent child-support payments. If you look in your answer, you ll find five separate entries for Michael Williams, each with a different date of birth. The lesson here is that you never, ever use a name as a unique identifier Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 2

The only reasonably reliable way we have is to identify people by their Social Security numbers. However, because we can rarely get those from public records, we have to use alternatives.

3 Ideally, we would use Social Security numbers to identify people uniquely, but we normally don t get them. That's why good reporters never, ever use a name as the only way to distinguish one person from another. The only reasonably reliable way we have is to identify people by their Social Security numbers. However, because we can rarely get those from public records, we have to use alternatives. Try repeating this, making it more distinct by adding the date of birth, city, or both. SELECT name, dob, count(*) GROUP BY name, dob ORDER by 3 desc Let s run that query. Our results should look like this: Using Having to Limit Results Just as we could set criteria, or where statements, to limit the fields returned, we can also set limits on aggregate functions in Group By statements, such as COUNT or SUM statements. This is a SQL expression known as Having. Let s practice by selecting only those Names that appear more than five times in the table. Here s how that query will look. SELECT name, count(name) FROM Orders GROUP BY name HAVING count(name)>5 Let s run that query and see how the Criteria statement limits the query results Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 3

4 PRACTICE EXERCISES 1. Who owes the most in child support? 2. In which city does he or she live? 3. Show a list of people who owe more than $50, From which city is the most child-support owed? 5. Who owes the most in Peoria? 6. Who owes for the greatest number of kids? Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 4

50 (second is David Tucker of Paris with $71,125). 3. Show a list of people who owe more than $50,000.

5 ANSWERS We can answer questions 1 and 2 together: 1. Who owes the most in child support? 2. In which city does he or she live? SELECT name, dob, city, sum(debt) GROUP BY name, dob, city ORDER BY sum(debt) desc Answer: Melvin Meeks of Chicago owes $100, (second is David Tucker of Paris with $71,125). 3. Show a list of people who owe more than $50,000. SELECT name, dob, city, sum(debt) GROUP BY name, dob, city Having sum(debt) > Answer: There are 14 people who owe more than $50, From which city is the most child-support owed? SELECT city, sum(debt) GROUP BY city ORDER BY sum(debt) desc Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 5

Answer: Chicago with $6,490,501.86 (followed by Peoria with $381,719.57). This shouldn t be surprising. It s by far the biggest city. You d need per capita debts to make it newsworthy.

6 Answer: Chicago with $6,490, (followed by Peoria with $381,719.57). This shouldn t be surprising. It s by far the biggest city. You d need per capita debts to make it newsworthy. Note that the second-biggest city is CHGO, perhaps a misspelling of Chicago? Hint: To get the values formatted as currency, use the menu item View, Properties while your cursor is anywhere in the Design View column holding the Sum. Change the Format to Currency: 5. Who owes the most in Peoria? SELECT name, dob, sum(debt) WHERE city = "PEORIA" GROUP BY name, dob ORDER BY sum(debt) desc Answer: Thomas Levi owes the most from Peoria, with $34, in debts. Keep in mind that if there are misspellings of Peoria, those orders will not be included in these totals. 6. Who owes for the greatest number of kids? If your instinct is to sum on the field num_kids, fight it! One person could have multiple orders for the same set of kids, so we don t want to add the number of kids. SELECT name, num_kids ORDER BY num_kids desc Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 6

For instance, in a payroll database you might want to create a field that calculates actual pay minus base pay. Access offers a powerful tool to create these kinds of fields.

7 Two people, Billey Turner and Earl Linnertz, apparently have orders for seven kids. We d want to check paper records to be sure. CALCULATIONS AND MAKE-TABLE QUERIES Sometimes, you will want to create new fields based on existing fields in your table. For instance, in a payroll database you might want to create a field that calculates actual pay minus base pay. Access offers a powerful tool to create these kinds of fields. In our table, let s calculate to see who has the largest child-support order per child. Remember that a person can have more than one order in the table. So, let s group by Name, DOB, Ord_Dat and Debt to isolate unique orders: SELECT name, dob, ord_dat, debt, num_kids, debt/num_kids AS PerKid FROM Orders WHERE num_kids>0 GROUP BY name, dob, ord_dat, debt, num_kids, debt/num_kids ORDER BY 6 desc Remember Jennifer LaFleur s rule on figuring how to calculate the number of X per Y. Just change the per to a division sign. If you run the query without the criteria that Num_Kids is greater than zero, you d get an error message (you can t divide by zero). See how giving the expression a field names makes the table easy to use? Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 7

8 Make-Table Queries A share of database reporting is taking a large set of records and culling it into a smaller table that you will spend most of your time analyzing. Here s how to turn your query results into a separate table. These are called make-table queries. You simply add two words in the SELECT line (INTO NEWTABLE, or whatever you want to name your new table): SELECT name, dob, ord_dat, debt, num_kids, debt/num_kids AS PerKid INTO Orders_perkid FROM Orders WHERE num_kids>0 GROUP BY name, dob, ord_dat, debt, num_kids, debt/num_kids ORDER BY 6 desc Joining Tables Tim Novak, a Post-Dispatch reporter who now works for the Chicago Sun-Times, knew that Illinois had been lax in collecting child support. He wanted to find out just how lax. He rhetorically asked this simple, but clever question: If Illinois is not aggressive in collecting child support from private employees, could it possibly be not collecting from people on its own payroll? The state payroll and the delinquent child-support list each contained thousands of records. So, a computer was needed to provide the necessary crunch. You already are familiar with the childsupport table. Now, let s open the state payroll table (Payroll) and browse it for a few moments to get a feel for what type of information it contains. Remember that you open an Access table by double-clicking on it. Record layout PAYROLL: Field name Type Description NAME Text Name of the employee in the form LNAME SUFFIX FNAME MNAME STREET Text CITY Text STATE Text ZIP Text JOB_TITLE Text AGENCY Text RATE Number Pay rate (hourly, weekly or monthly) YTD_GROSS Number Year-to-date actual pay Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 8

Note that the pay rate isn t comparable from one employee to another. Sometimes it s expressed as an hourly rate, other times it s expressed as a monthly rate.

9 Note that the pay rate isn t comparable from one employee to another. Sometimes it s expressed as an hourly rate, other times it s expressed as a monthly rate. So if you want to know about pay, you ll have to use the YTD_GROSS field. You should also note the format of the name, along with any useful fields for identifying people. In particular, pay attention to what s missing: Some employees zip codes and addresses. Here s what the table looks like: When you join, or match, data in two tables, you link the two tables on fields with common values. Ideally, you would want a unique identifier in each table, such as a Social Security number. But this is not an ideal world. To join two tables in Access, you start a new query just like you would with one table. But here s a key difference: Your FROM statement should have both tables. We also have to tell Access what fields we want to match on. In this case, we ll start with a broad match, on name only. SELECT *, payroll WHERE orders.name=payroll.name Let s run that query. Look carefully at our results. Does something seem amiss? Take a look at Michael Adams. Remember the warning about not using names as unique identifiers? We probably have different people with the same name. Now, let s tighten our join by also matching on the Street fields. Then, select the ZIP codes from each field to help us double-check the data. Now, let s avoid records where the addresses are suppressed. We will set a Where (criteria) condition on the Street field of the payroll table. We ll use a wildcard (*) and a not equal sign <> to save us typing. Our query should look like this: SELECT *, payroll WHERE (orders.name = payroll.name) and (orders.street = payroll.street) and (orders.street not like "Address Supp*" or payroll.street not like "Address Supp*") Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 9

We matched 241 records. You can always tell how many records the query returned by looking in the bottom left-hand corner of the query results. Let s run the query a different way.

10 We matched 241 records. You can always tell how many records the query returned by looking in the bottom left-hand corner of the query results. Let s run the query a different way. Let s join on Name and Zip from the two fields. We will delete the join on Street for now. SELECT *, payroll WHERE orders.name = payroll.name and orders.zip = payroll.zip Let s look at our results. We got 269 hits. See how some of the street names are slightly different, like the following? Let s keep the join on Name and Zip and crunch the data a little further. Let s make a new table (a make-table query) of state employees who we suspect are delinquent in child support. Select the Name, Street and ZIP file from each table, plus DOB and Debt from Orders and Agency, Job_Title and YTD_Gross from Payroll. Call the new table something like Matches. SELECT Payroll.name, Payroll.street, Payroll.zip, Orders.dob, Orders.debt, Payroll.agency, Payroll.job_title, Payroll.ytd_gross INTO Matches FROM Payroll, Orders WHERE Orders.name = Payroll.name AND Orders.zip = Payroll.zip Let s carefully look for any bad records, again, in this table. Do you find any? Notice that there are two Robert Jones: better make some adjustments to find out which one is the correct. (Hint: check payroll, then delete a record.) Now you have 268 matches. Now that we think are records are reasonably clean, let s use the new, smaller table to find out which state employees owe the most, where they work and what they do. 1. Let s select these fields: Name, Job_Title, Agency and SUM(Debt) 2. Group By. We will group by Name, Job_Title and Agency 3. Order By, or Sort. Sort by descending SUM(Debt), so we know who owes the most Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 10

SELECT name, job_title, agency, sum(debt) FROM Matches GROUP BY name, job_title, agency ORDER BY 4 desc Answer: Luther Billops, a building service worker at State Community College owes $32,315.94.

11 SELECT name, job_title, agency, sum(debt) FROM Matches GROUP BY name, job_title, agency ORDER BY 4 desc Answer: Luther Billops, a building service worker at State Community College owes $32, PRACTICE EXERCISES 1. Which state employee has the most orders filed against him or her? How many? 2. What is the total amount of delinquent child support owed by Illinois state employees? 3. Which state employees owe the least? What are those amounts? 4. From which agency do employees have the most outstanding child-support orders? 5. From which agency do employees owe the most? 6. Which type of employee owes the most in back child support? Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 11

What is the total amount of back child support owed by all state employees? SELECT sum(debt) FROM matches Answer: $ 826,890.33 3. Which state employees owe the least?

12 ANSWERS 1. Which state employee has the most orders against him or her? SELECT name, job_title, agency, count(*) FROM Matches GROUP BY name, job_title, agency ORDER BY 4 desc Answer: Cooper Davis, a police officer, with seven. 2. What is the total amount of back child support owed by all state employees? SELECT sum(debt) FROM matches Answer: $ 826, Which state employees owe the least? SELECT name, dob, sum(debt) FROM matches GROUP BY name, dob ORDER BY 3 Answer: Charles Montgomery owes 25 cents, and John Longoria owes 50 cents. 4. From which agency do employees have the most orders filed? SELECT agency, count(*) FROM Matches GROUP BY agency ORDER BY 2 desc Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 12

Answer: Mental Health, with 87. Public Aid has 45. 5. From which agency do employees owe the most?

$248,426.97 (Central Management Services is next with $111,414.30). 6.

SELECT job_title, sum(debt) FROM Matches GROUP BY job_title ORDER BY 2 desc Answer: Support Service

13 Answer: Mental Health, with 87. Public Aid has From which agency do employees owe the most? SELECT agency, sum(debt) FROM Matches GROUP BY agency ORDER BY 2 desc Answer: Mental Health with $248, (Central Management Services is next with $111,414.30). 6. From which type of employee is the most back child support owed? SELECT job_title, sum(debt) FROM Matches GROUP BY job_title ORDER BY 2 desc Answer: Support Service Worker II with $80, (Graduate Assistant Faculty is next with $ 71,393.99) Duplication prohibited without permission from Investigative Reporters and Editors, Inc. 13

Microsoft Access 2007 Lesson 2: Retrieving Information from a Database

Microsoft Access 2007 Lesson 2: Retrieving Information from a Database In this lesson you will learn how to construct queries to retrieve information from a database. It uses the example database (ExampleDB.accdb)