AWS CloudWatch Scheduled Event and Lambda Function

A.

In the Range Check control data should not exceed a predefined range of values For CISA exam you should know below mentioned data validation edits and controls Sequence Check " The control number follows sequentially and any sequence or duplicated control numbers are rejected or noted on an exception report for follow-up purposes.

For example, invoices are numbered sequentially.

The day's invoice begins with 12001 and ends with 15045

If any invoice larger than 15045 is encountered during processing, that invoice would be rejected as an invalid invoice number.

Limit Check " Data should not exceed a predefined amount.

For example, payroll checks should not exceed US $ 4000

If a check exceeds US $ 4000, data would be rejected for further verification/authorization.

Validity Check " Programmed checking of data validity in accordance with predefined criteria.

For example, a payroll record contains a field for marital status and the acceptable status codes are M or S.

If any other code is entered, record should be rejected.

Range Check " Data should not exceed a predefined range of values.

For example, product type code range from 100 to 250

Any code outside this range should be rejected as an invalid product type.

Reasonableness check " Input data are matched to predefined reasonable limits or occurrence rates.

For example, a widget manufacturer usually receives an order for no more than 20 widgets.

If an order for more than 20 widgets is received, the computer program should be designed to print the record with a warning indicating that the order appears unreasonable.

Table Lookups " Input data comply with predefined criteria maintained in computerized table of possible values.

For example, an input check enters a city code of 1 to 10

This number corresponds with a computerize table that matches a code to a city name.

Existence Check " Data are entered correctly and agree with valid predefined criteria.

For example, a valid transaction code must be entered in transaction code field.

Key verification " The keying process is repeated by a separate individual using a machine that compares the original key stroke to the repeated keyed input.

For ex.

the worker number is keyed twice and compared to verify the keying process.

Check digit " a numeric value that has been calculated mathematically is added to a data to ensure that original data have not been p[ altered or incorrect, but Valid, value substituted.

This control is effective in detecting transposition and transcription error.

For ex.

A check digit is added to an account number so it can be checked for accuracy when it is used.

Completeness check " a filed should always contain data rather than zero or blanks.

A check of each byte of that field should be performed to determine that some form of data, or not blanks or zeros, is present.

For ex.

A worker number on a new employee record is left blank.

His is identified as a key in filed and the record would be rejected, with a request that the field be completed before the record is accepted for processing.

Duplicate check " new transaction is matched to those previously input to ensure that they have not already been entered.

For ex.

A vendor invoice number agrees with previously recorded invoice to ensure that the current order is not a duplicate and, therefore, the vendor will not be paid twice.

Logical relationship check " if a particular condition is true, then one or more additional conditions or data input relationship may be required to be true and consider the input valid.

For ex.

The hire data of an employee may be required to be true and consider the input valid.

For ex.

The hire date of an employee may be required to be more than 16 years past his her date of birth.

The following were incorrect answers: Table Lookups " Input data comply with predefined criteria maintained in computerized table of possible values.

For example, an input check enters a city code of 1 to 10

This number corresponds with a computerize table that matches a code to a city name.

Existence Check " Data are entered correctly and agree with valid predefined criteria.

For example, a valid transaction code must be entered in transaction code field.

Reasonableness check " Input data are matched to predefined reasonable limits or occurrence rates.

For example, a widget manufacturer usually receives an order for no more than 20 widgets.

If an order for more than 20 widgets is received, the computer program should be designed to print the record with a warning indicating that the order appears unreasonable.

The answer to the question is A. Range Check.

Data validation is the process of ensuring that the input data is accurate, complete, and reasonable. One of the data validation controls is the Range Check, which validates input data against predefined range values.

Range check is a data validation control that verifies whether the input data falls within a predefined range of acceptable values. It checks whether the input value is within the lower and upper limits of the expected range. For example, if a data field expects a value between 0 and 100, the range check would verify whether the entered value falls within this range.

Table lookups and Existence check are also data validation controls. Table lookups involve checking whether the input data exists in a predefined list of valid values. Existence check, on the other hand, verifies whether the entered data exists in the database or file system.

Reasonableness check is a data validation control that verifies whether the input data is reasonable and logical. It checks whether the entered data makes sense or not. For example, if a customer's age is entered as 150, the reasonableness check would identify this as an error since it is not reasonable for a person to be that old.

In conclusion, range check is a data validation control that ensures the input data falls within a predefined range of acceptable values. It is one of the important controls used to validate input data and ensure the accuracy and completeness of data.