Start Access: Open The Downloaded File Named Exploring

start Access Open The Downloaded Access File Namedexploring A03 Grad

Create various queries in Microsoft Access based on specified tables, including displaying client details, calculating account longevity, summing savings balances by client, filtering based on criteria, and computing loan payments. Save each query with the specified names, and finally close all objects, the database, and exit Access.

Paper For Above instruction

The task involves creating multiple queries within a Microsoft Access database, specifically focusing on the tables Clients and Accounts. The objectives are to extract, calculate, aggregate, filter, and analyze data related to clients' personal details, account balances, account longevity, and loan payments. Each step builds upon previous steps, requiring familiarity with Access Query Design, expressions, sorting, grouping, totaling, and the use of functions such as PMT for financial calculations.

Step 1: Opening the Access File

The initial step involves opening the downloaded Access database file named "exploring_a03_grader_a1." This file contains the relevant tables needed for subsequent query creation. Ensuring the database opens correctly is essential before proceeding.

Step 2: Creating the Account Longevity Query

Using Query Design, add the Clients and Accounts tables. From the Clients table, select the First Name and Last Name fields; from the Accounts table, select the Savings Balance and Account Open Date fields. Sorting the results by Savings Balance in descending order enables quick identification of clients with the highest savings. Next, include a calculated field, labeled AccountTime, which computes the number of days since each account was opened. The calculation uses the DateDiff function, subtracting the Account Open Date from the fixed date December 31, 2017, with the date enclosed in # symbols to denote a date in Access. Format the AccountTime in General Number format. Save this query as Account Longevity.

Step 3: Summing Client Savings

Create a second query with Query Design, including the Clients table (First and Last Names) and Accounts table (Savings Balance). Implement grouping to aggregate savings balances by client, effectively summing total retirement account balances for each client. Sorting by total savings in descending order highlights clients with the highest total balances.

Step 4: Totals and Filtering

Switch to Datasheet view for the above query. Add totals to display the count of clients and the average of total savings balances. Save this as Total Balances By Client. Create a copy of this query, rename it to Total Balances By State>, and modify it by removing client names. Instead, add grouping by the client’s state, and sort states in ascending order. Apply criteria to include only clients with retirement savings balances of $10,000 or more. Save and close this query.

Step 5: Filtering Clients with Specific Balances

Design a new Query to display client first and last names, state, and savings balances, but only for clients with balances under $15,000 — achieved by adding appropriate criteria. This step filters the data for clients who have moderate savings accounts.

Step 6: Calculating Loan Payments

Next, create a reference for a new field named LoanPayment using the Expression Builder. Use the PMT function to calculate the monthly payment for a 2-year loan, paid monthly, with an annual interest rate of 5%. The principal amount (present value) is the $25,000 purchase price minus the client’s savings balance (e.g., if savings are $5,000, the loan amount is $20,000). The formula ensures the payment is displayed as a positive number. Change this field’s format to Currency and set its caption to Loan Payment. Save the query as Monthly Loan Payments.

Step 7: Finalization and Closure

After completing all queries, close all database objects, then close the database itself. Finally, exit Microsoft Access. The completed database with all queries should be submitted as directed, fulfilling the specified tasks with accurate data handling and proper query design techniques.

References

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