--- title: "KDD phases with example" subject: "Data Mining" chapter: 1 key: "semester_7/data_mining:kdd-phases-example" source: https://www.bctengineer.com/q/semester_7/data_mining/kdd-phases-example site: BCT Engineering --- # KDD phases with example Data Mining · Chapter 1: Introduction - Asked in: 2066 Bhadra, 2+8 marks; year not given, 2+8 marks; 2063, 2+8 marks; 2065 Baisakh; year not given, 3 marks; year not given (asked 3 times) - Video: [Data Mining & Business Intelligence | Tutorial #1 | The KDD Process](https://www.youtube.com/watch?v=U-hUnxuaw7w) — RANJI RAJ - Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14 - Page: https://www.bctengineer.com/q/semester_7/data_mining/kdd-phases-example - Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-1 ## Question How do you relate KDD with data mining? Is KDD a data mining? Explain the phases of KDD with example. ## Short answer KDD is the full process of turning raw data into knowledge; data mining is only its core step, so KDD is not just data mining. Its phases are cleaning, integration, selection, transformation, mining, evaluation, and presentation. Example: supermarket sales are cleaned, merged, basket-transformed, mined with Apriori, evaluated by support/confidence, and presented as buying rules. ## Answer **KDD (Knowledge Discovery in Databases)** is the complete process of discovering useful knowledge from large data. **Data mining** is only one step (the core step) of this process, so KDD is not the same as data mining: data mining is a part of KDD, while KDD also includes preparation of data before mining and interpretation of results after mining. #### Relation between KDD and data mining - KDD is the overall, multi-step, iterative process; data mining is the step that applies algorithms to find patterns. - KDD starts with raw data and ends with usable knowledge; data mining starts with prepared data and ends with patterns. - In many books and in industry, the two terms are used loosely as synonyms, but strictly data mining is one phase of KDD. #### Phases of KDD ```text Raw data -> [1 Data cleaning] -> [2 Data integration] -> [3 Selection] -> [4 Transformation] -> [5 Data mining] -> [6 Pattern evaluation] -> [7 Knowledge presentation] ``` 1. **Data cleaning**: remove noise and inconsistent data, fill missing values. 2. **Data integration**: combine data from several sources (databases, files, web) into one store. 3. **Data selection**: retrieve only the data relevant to the analysis task. 4. **Data transformation**: convert data into forms suitable for mining (normalisation, aggregation, generalisation). 5. **Data mining**: apply algorithms (classification, clustering, association) to extract patterns. 6. **Pattern evaluation**: identify the truly interesting patterns using measures such as support and confidence. 7. **Knowledge presentation**: show the knowledge to the user with visualisation and reports. #### Example: supermarket A supermarket chain wants to know which products are bought together. 1. Cleaning: remove duplicate bills and fix missing product codes. 2. Integration: merge billing data of all branches with the customer-card database. 3. Selection: choose only the last 12 months of sales transactions. 4. Transformation: convert each bill into a list of items bought (basket format). 5. Mining: run the Apriori algorithm to find frequent itemsets. 6. Evaluation: keep rules with support ≥ 2% and confidence ≥ 60%, e.g. {bread} → {butter} (80%). 7. Presentation: show the rules to the manager, who places butter near bread and runs combo offers. ## Check yourself The answer's key points as multiple-choice questions, with the correct option and why. 1. How is data mining related to KDD? A. Data mining is the core pattern-finding step within the larger KDD process B. KDD only covers data cleaning C. KDD is one step inside data mining D. They are identical processes Answer: A. KDD is the whole multi-step process; data mining is only the step that applies algorithms to find patterns. (Key point: KDD vs data mining) 2. Which sequence of KDD phases is correct? A. Selection, cleaning, mining, transformation B. Cleaning, integration, selection, transformation, mining, evaluation, presentation C. Mining, cleaning, evaluation, integration D. Integration, mining, cleaning, presentation Answer: B. Data are prepared (clean, integrate, select, transform) before mining, then evaluated and presented. (Key point: Order of KDD phases) 3. In the supermarket example, what happens in the pattern evaluation phase? A. Apriori finds frequent itemsets B. Rules are kept only if they meet support and confidence thresholds C. Duplicate bills are removed D. Bills are converted into basket format Answer: B. Evaluation filters the truly interesting rules using measures such as support >= 2% and confidence >= 60%. 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