Data Mining in DBMS 

 Data Mining kya hota hai?

Data Mining ka matlab hai bade data me se useful patterns, trends aur knowledge nikalna.

 Ye bilkul waise hai jaise pahadon me se sona nikalna – data ke samundar me se valuable cheezein dhundhna.

 Simple Definition:

Data Mining ek process hai jisme hum bade data sets me se patterns, relationships, ya useful information find karte hain using statistical ya machine learning techniques.

 Data Mining kyu zaroori hai?

Aaj ke time me companies ke paas huge data hota hai — GBs ya TBs me. Lekin wo raw data akela kuch kaam ka nahi hota.

Data mining help karta hai:

• Business decision lene me

• Customer behavior samajhne me

• Future predict karne me

• Fraud detect karne me

• Recommendations dene me (jaise Netflix, Amazon)

 Data kaha store hota hai?

Data mining ke liye data in sources se aata hai:

• Databases (DBMS)

• Data Warehouses

• Files, logs

• Web data

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 DBMS aur Data Mining 

 Data Mining Process ke Steps

KDD Process (Knowledge Discovery in Database):

Breakdown:

1. Data Cleaning

   • Galat ya missing data hataana

   • Example: “NULL” values remove karna

2. Data Integration

   • Alag-alag sources ka data jodna

   • Example: Sales aur customer DB merge karna

3. Data Selection

   • Sirf relevant data choose karna

   • Example: Sirf 2023 ke sales record lena

4. Data Transformation

   • Data ko mining ke layak banana

   • Example: Values ko normalize karna

5. Data Mining

   • Algorithms use karke patterns find karna

   • Example: “25-30 age ke log product X lete hain”

6. Pattern Evaluation

   • Jo patterns mile wo useful hain ya nahi, check karna

   • Example: Random patterns hata dena

7. Knowledge Presentation

   • Result ko charts, graphs ya reports me dikhana

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 Data Mining ke Do Main Types

1. Descriptive

Jo data describe karta hai
Example: “Zyada log 6–9 PM ke beech shopping karte hain”

2. Predictive

Jo data se future predict karta hai
Example: “Customer X agle mahine service band kar sakta hai”

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 Common Data Mining Techniques

 Example: Association Rule Mining

Suppose ye transactions hain:

Rule milta hai:

“Jo log Milk aur Bread lete hain, wo aksar Butter bhi lete hain.”

Use:

• Product recommend karne me

• Store layout decide karne me

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 Tools jo Data Mining ke liye use hote hain:

• Weka – Beginner friendly tool

• Python / R – Coding wale tools (powerful)

• RapidMiner, Orange – Drag & Drop type tools

• SQL – With mining extensions

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 Data Mining ke Fayde

1. Smart business decisions

2. Customer ko samajhna

3. Fraud detect karna

4. Cost kam karna

5. Better marketing plans

 Data Mining ki Challenges

• Privacy aur security issues

• Data cleaning ka time lagta hai

• Big data pe kaafi slow ho sakta hai

• Patterns galat interpret karna

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 Summary