Chapter 3 Data Control Ensure the Accurate and Complete data is entering into the data processing system.

Slides:

Advertisements

Similar presentations

Verification & Validation

Advertisements

Data. What is an Input Device? List three (3) examples of Input Devices. Define the term Data. In what phase of the DPLC would you find data? 1/18/2012Ms.

©G. Millbery 2003Data, Information, Knowledge and Processing Slide 1 Validation  Making sure that the data value entered is sensible and reasonable 

2.2 Validation & Verification

Commercial Data Processing Lesson 2: The Data Processing Cycle.

Commercial Data Processing Lesson 3: Data Validation.

3.1 Data and Information –The rapid development of technology exposes us to a lot of facts and figures every day. –Some of these facts are not very meaningful.

Validation and Verification Today will look at: The difference between accuracy and validity Explaining sources of errors and how they could be overcome.

Validation and Verification

RNJ 10/02/091 3 Computing System Fundamentals 3.6 Errors Prevention and Detection.

Input Design Objectives

Topics Covered: Data preparation Data preparation Data capturing Data capturing Data verification and validation Data verification and validation Data.

Encoding, Validation and Verification Chapter 1. Introduction This presentation covers the following: – Data encoding – Data validation – Data verification.

It is physically impossible for any data recording or transmission medium to be 100% perfect 100% of the time over its entire expected useful life. As.

GCSE ICT Checking data. Why do errors happen? Computers do not make mistakes. However if incorrect data is put in errors happen. In ICT this is called.

3.2 Data Checking.

Data entry: Validation

Checking data GCSE ICT.

Checking data Chapter 7 Prepared by:Sir Mazhar Javed.

Information Processing and Presentation by Rico Yu.

Objectives of Control The objectives of control are:  To ensure that all data are processed  To preserve the integrity of maintained data  To detect,

Creating a Database Designing Structure, Capturing and Presenting Data.

System Development Lifecycle Verification and Validation.

1.The Nature, Impact and Issues of Information Technology 1.6Strategies used to Prevent Deliberate and Accidental Illegal Actions.

Social and Ethical Issues. Social & Ethical Issues Social and ethical issues arise from the processing of data into information. There are many issues.

AS computing Validation and verification. Introduction It is important to maintain the integrity of any database of information. Any data item must always.

MAT 105 Spring  An identification number is a sequence of letters and/or numbers that identifies an object, person, place, or concept  The number.

DATA ERRORS. Introduction The processing of incorrect data can produce ridiculous and embarrassing output. Errors can take time to sort out and can be.

CIT PowerPoint presentation Group 4. Unit 1, Chapter 2 Basic Concept on Data DATA AND INFORMATION What is data? Data consists of all sorts of unorganised.

Verification & Validation F451 AS Computing. Why check data? It’s useless if inaccurate. Also, wrong data: Can be annoying Can cost a fortune Can be dangerous.

AS Level ICT Data entry: Problems with errors. Garbage in; Garbage out If incorrect data is entered into a data management system, the results of any.

Commercial Data Processing Credit. Management Information CDP makes it easier for managers to control and process the information that is needed in the.

Week 1 Theory 2 B usiness I nformation S ystems Batch Processing Assignment 6 - Batch Processing 1 Batch Processing Method.

Verification & Validation. Batch processing In a batch processing system, documents such as sales orders are collected into batches of typically 50 documents.

Review of Data Capture. Input Devices What input devices are suitable for data entry? Keyboard Voice Bar Code MICR OMR Smart Cards / Magnetic Stripe cards.

1 3 Computing System Fundamentals 3.6 Errors Prevention and Recovery.

Errors!. Where do errors occur? Anywhere data is transferred, processed, stored, etc. Input user error Storage magnetic hard drive errors physical tampering.

Data Collection. Data Capture This is the first stage involved in getting data into a computer Various input devices are used when getting data to the.

Data Verification and Validation

1 AQA ICT AS Level © Nelson Thornes 2008 Good quality data and information Data terms.

Data Validation.

Data Management Data Verification Data Validation.

CH. 6 SELF CHECK QUIZ ARE YOU PREPARED FOR THE TEST?

Input Devices By Mrs. Gonzales. All the input, output and storage devices connected to and dependent on a computer for operation are called peripherals.

Math for Liberal Studies. What is an identification number?  An identification number is a sequence of digits and/or numbers that identifies an object,

Verification & Validation

Validation & Verification Today will look at: The difference between accuracy and validity Explaining sources of errors and how they could be overcome.

Programming Logic and Design Fourth Edition, Comprehensive Chapter 10 Using Menus and Validating Input.

Input, Output and Processing.. What data needs to be input into the system? Identify the sources – i.e. where does the data come from? What is the volume.

 At the end of the class students should:  distinguish between data and information.  explain the characteristics and forms of Information Processing.

Data Capture Forms What are they?. Example 1 Example 2.

GCSE ICT LESSON 5 Booklet Sections: 6 & 7 Data Capture & Checking Data.

Validation and verification 1.2

2.8 Error Detection and Correction

DATA COLLECTION Data Collection Data Verification and Validation.

Error Detection and Correction

Validation Bury College.

SECTION 5: INFORMATION PROCESSING

IT Applications Theory Slideshows

Objectives TO UNDERSTAND THAT CAPTURING DATA IS VALIDATED AND VERIFIED TO CHECK THAT IT IS REASONABLE AND CORRECT.

How can errors in data occur when using an ICT system?

Chapter 7: Input Validation

Verification and Validation

Commercial Data Processing

Systems Development Lifecycle

Validation and Verification

2.8 Error Detection and Correction

Presentation transcript:

Chapter 3 Data Control

Ensure the Accurate and Complete data is entering into the data processing system.

Sources of error Data Collection errors Enter wrong information onto the source documents. E.g.. Poor handwriting Data Preparation errors Transcription error Data on the source document are copied incorrectly. Data Input errors Typing error

Preventive Measure: Data Verification Data Validation

Data Verification Checking the accuracy of data has been copied from one medium to another. Usually takes place at the DATA PREPARATION or DATA INPUT stage.

Verification Process: It involves two operators to type the same set of data independently. First operator types in the data. Second operator re-enters all the data. A computer program compares both input. Alert the operator if Discrepancies occurs.

Data Validation Ensure data is valid and acceptable for data processing. Done by validation program.

Data Validation Methods Presence check Range check Data type check Consistency check Control total(batch total) Hash total Check digit

Data Validation Method Presence Check Ensure the data are present. Range Check Ensure data lie within a certain range. Data type Check Ensure data type is correct.

Data Validation Check Digit is an extra digit appended to a code consisting of a series of numbers or characters. Detect errors arising from transcription.

Modulo 11 Check / 11 = 4874 … 8 Remainder = 8 which equals to the check digit. The input data is correct (8) Check digit

Modulo 11 Check / 11 = 4875 … 2 Remainder = 2 which NOT equals to the check digit(8).The input data is INCORRECT. Check digit (8) Original 53627(8) Input

Modulo 11 Check / 11 = … 0 Remainder = 0 which equals to the check digit(0).The input data is also considered as CORRECT but in fact it is incorrect. Check digit (0) Original (0) Input

Weighted modulo 11 check A weight is given to each digit X 3 = 6 X 2 = 4 X 4 = 24 X 5 = 15 X 6 = = 7, remainder=2 Subtract the remainder from 11 to get the check digit, 11 – 2 = 9 (9)

Weighted modulo 11 check for Account Number A weight is given to each digit X 3 = 6 X 2 = 4 X 4 = 24 X 5 = 15 X 6 = = 8, remainder=0 So, the account number is valid. (9) X 1 = 9

Weighted modulo 11 check for ID card number A weight is given to each digit. Z X 3 = 3 X 2 = 4 X 4 = 28 X 5 = 15 X 6 = 30 (3) X 7 = 28 X 8 = 208 A = 1 B = 2 C = 3. Z = …8…8 Check digit = 11 – 8 = 3

Differences between Data Validation and Data Verification Data VerificationData Validation Checking data that have been copied from one medium to another. Check validity of data before they are processed. Include Invalid data after data verification. Exclude Invalid data after data validation. Takes place at data preparation stage. Takes place at data input stage (prior to processing).