22PCOAM21 Session 2 Understanding Data Source.pptx
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22PCOAM21 Session 2 Understanding Data Source.pptx
- 1. 07/26/2025 1 Department of Computer Science & Engineering (SB-ET) III B. Tech -II Semester DATAANALYTICS SUBJECT CODE: 22PCOAM21 AcademicYear : 2024-2025 By Dr.M.Gokilavani GNITC Department of CSE (SB-ET)
- 2. 07/26/2025 Department of CSE (SB-ET) 2 22PCOAM21 DATAANALYTICS UNIT – I Syllabus Data Management: Design Data Architecture and manage the data for analysis, understand various sources of Data like Sensors/Signals/GPS etc. Data Management, Data Quality (noise, outliers, missing values, duplicate data) and Data Preprocessing &Processing. Course Prerequisites 1. Database Management Systems. 2. Knowledge of probability and statistics.
- 3. 07/26/2025 3 TEXTBOOK: • Student’s Handbook for Associate Analytics - II, III. • Data Mining Concepts and Techniques, Han, Kamber, 3rd Edition, Morgan Kaufmann Publishers. REFERENCES: • Introduction to Data Mining, Tan, Steinbach and Kumar, Addision Wisley, 2006. • Data Mining Analysis and Concepts, M. Zaki and W. Meira • Mining of Massive Datasets, Jure Leskovec Stanford Univ. Anand Rajaraman Milliway Labs, Jeffrey D Ullman Stanford Univ. No of Hours Required: 13 Department of CSE (SB-ET) UNIT - I LECTURE - 02
- 4. 07/26/2025 Department of CSE (SB-ET) 4 Data & Data Collection • Data is a collection of measurements and facts. • A tool that helps an individual or a group of individuals reach a sound conclusion by providing them with some information. • Data collection serves as the critical first step in this process, laying the foundation for extracting meaningful insights from raw information. • Structured like numerical records • Unstructured like text, audio, or video, organizations can transform raw data into actionable knowledge. • In the process of big data analysis, “Data collection” is the initial step before starting to analyze the patterns or useful information in the data. UNIT - I LECTURE - 02
- 5. 07/26/2025 Department of CSE (SB-ET) 5 Data Collection • The data that is collected is known as raw data, which is not useful now, but after cleaning the impure and utilizing that data for further analysis forms information, the information obtained is known as “knowledge”. • There are two types • Qualitative data • Quantitative data • Qualitative data which is a group of non-numerical data such as words, sentences mostly focus on behavior and actions of the group. • Quantitative data which is in numerical forms and can be calculated using different scientific tools and sampling data. UNIT - I LECTURE - 02
- 6. 07/26/2025 Department of CSE (SB-ET) 6 Data Collection The actual data is then further divided mainly into two types known as: • Primary data • Secondary data UNIT - I LECTURE - 02
- 8. 07/26/2025 Department of CSE (SB-ET) 8 Primary Data • The data which is Raw, original, and extracted directly from the official sources is known as primary data. • This type of data is collected directly by performing techniques such as questionnaires, interviews, and surveys. • The data collected must be according to the demand and requirements of the target audience on which analysis is performed otherwise it would be a burden in the data processing. • Few methods of collecting primary data • Interview method - E.g: Telephone, face to face, email, etc. • Survey method - E.g: Text, audio, or video • Observation method – E.g: Results • Experimental Method – E.g: Research, and Investigation UNIT - I LECTURE - 02
- 9. 07/26/2025 Department of CSE (SB-ET) 9 Secondary Data • Secondary data is the data which has already been collected and reused again for some valid purpose. • This type of data is previously recorded from primary data and it has two types of sources named • Internal source • External source • Other Resources such as Sensors data, Satellite Data, Web traffic etc., UNIT - I LECTURE - 02
- 10. 07/26/2025 Department of CSE (SB-ET) 10 Topics to be covered in next session 3 • Data Quality (noise, outliers, missing values, duplicate data) Thank you!!! UNIT - I LECTURE - 02