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# Data processing and analysis final

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### Data processing and analysis final

1. 1. MMS-A NAMITA AMALE -01 SACHIN CHAUDHARY-05 PRANOTI VARTAK-38 PRIYA KUMAR-28 RUPAM THAKKAR-36 ARYA KULANGARATHODI -15 SIDDHESH SONAWANE-32 SUSHIL TAMBITKAR-35 Data Processing & Analysis
2. 2. Contents  Data & Types  Information  Data Anaysis  Data Processing  Steps in Data Processing  Types Of Data Processing  Data Processing Cycle
3. 3. Data Data  The word data is derived from Latin language. It is plural of Datum. Data is any collection of facts of figures. The data is the raw material to be processed by a computer. Example  Names of students, marks obtained in the examination, designation of employees, addresses, quantity, rate, sales figures or anything that is input to the computer is data. Even pictures, photographs, drawings, charts and maps can be treated as data. Computer processes the data and produces the output or result
4. 4. Types of Data Numeric Data Character Data String Data Graphical Data
5. 5. Data & Data Set The information that you collect from an experiment, survey is referred to as your data. A data set is a representation of data, defining a set of variables" that are measured on a set of cases." Variable A variable is any characteristic of an object that can be represented as a number. The values that the variable takes will vary when measurements are made on different objects or at different times. Case Recorded information about an object we observe a case.
6. 6. Information A collection of data which conveys some meaningful idea is information. It may provide answers to questions like who, which, when, why, what, and how. or Observations and recordings are done to obtain data, while analysis is done to obtain information
7. 7. Data Analysis  Steps in Data Analysis Data Collection & Preparation  Exploration of Data Data Analysis Method (s)/ Techniques
8. 8. Data Preparation Collect data Preparation of code books Set up structure of data Enter data Screen data for errors
9. 9. Exploration Of Data  Graphs Descriptive stats
10. 10. Data Analysis Techniques  Comparing means- Statistical testing  Correlations  Text Analytics
11. 11. Data Processing
12. 12. Data Processing  The processing of converting data into useful information.  Data processing system  - the activities, equipment & personnel invovled. Data Process Information
13. 13. Data Processing Data processing: Any operation or set of operations performed upon data, whether or not by automatic means, such as collection, recording, organization, storage, adaptation or alteration to convert it into useful information.
14. 14. Data VS Information  Information  Data 120557 Date 12/05/57 Time 12:05:57 Money 120,557
15. 15. Examples of Data Processing  Organizing examination records  The subject teacher collects the marked examination papers  The subject scores are entered on score sheet  The score sheet are given to the class teacher  The class teacher calculate the total & the average score of each student  A report card for each student is produced ,master report sheet for the class is kept for future reference.
16. 16. Steps of data processing There are 5 steps included in Data processing:  Editing  Coding  Classification  Data Entry  Validation  Tabulation
17. 17. Editing  Editing of data is a process of examining the collected raw data to detect errors and omissions and to correct these when possible.  With regards to stages: 1. Field Editing 2. Central Editing
18. 18. Coding  Coding refers to process of assigning numerals or other symbols to answers so that responses can be put into a limited number of categories or classes.
19. 19. Classification  Data having a common characteristics are placed in one class and in this way the entire data get divided into a number of groups or classes.  Types: 1. Classification according to attributes 2. Classification according to class intervals
20. 20. Data Entry  After the data has been properly arranged and coded, it is entered into the software that performs the eventual cross tabulation.  Data entry professionals do the task efficiently.
21. 21. Validation  After the cleaning phase, comes the validation process.  It refers to the process of thoroughly checking the collected data to ensure optimal quality levels.  All the accumulated data is double checked in order to ensure that it contains no inconsistencies and is relevant.
22. 22. Tabulation  Tabulation is the process of summarising raw data and displaying the same in compact form for further analysis.  Benefits: 1. It conserves soace and reduces explanatory statement to a minimum 2. It facilitates the process of comparison 3. It facilitates the summation of items and detection of errors 4. It provides a basis for various statistical computations
23. 23. Types Of Data Processing Manual data Processing EDP Real time Processing Batch Processing
24. 24. Once data is collected, it is processed to convert it into useful information. The data is processed again and again until the accurate result is achieved. This is called data processing cycle. The data processing is very important activity and involves very careful planning. Usually, data processing activity involves three basic activities. 1. Input 2. Processing 3. Output Data Processing Cycle
25. 25. Input Processing Output Verification Classification Retrieval Communication Conversion Storing Calculation Storing Coding Summarizing Data Processing Cycle