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Data Warehouse and Data Mining

Data Warehouse and Data Mining Syllabus

Yeh Data Warehouse and Data Mining ka complete syllabus list format me diya hai, bina explanation ke — sirf topics list: PART 1: Data Warehouse Syllabus Li…

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SQLDataDev Editorial Team

Mar 19, 2026 3 min read

Yeh Data Warehouse and Data Mining ka complete syllabus list format me diya hai, bina explanation ke — sirf topics list:

PART 1: Data Warehouse Syllabus List

1. Introduction to Data Warehouse

  • What is Data Warehouse
  • Characteristics of Data Warehouse
  • OLTP vs OLAP
  • Operational Database vs Data Warehouse
  • Benefits of Data Warehouse
  • Use cases

2. Data Warehouse Architecture

  • Single-tier architecture
  • Two-tier architecture
  • Three-tier architecture
  • Components of Data Warehouse
  • Source systems
  • Staging area
  • Data warehouse storage
  • Presentation layer

3. ETL Process

  • ETL Overview
  • Extract process
  • Transform process
  • Load process
  • ETL vs ELT
  • Full load
  • Incremental load
  • Change Data Capture (CDC)
  • Data cleansing
  • Data validation

4. Data Warehouse Modeling

  • Dimensional modeling
  • Fact tables
  • Dimension tables
  • Measures
  • Attributes
  • Grain definition

5. Schema Design

  • Star schema
  • Snowflake schema
  • Galaxy schema (Fact constellation)
  • Schema comparison

6. Keys in Data Warehouse

  • Primary key
  • Foreign key
  • Surrogate key
  • Natural key
  • Composite key

7. Slowly Changing Dimensions (SCD)

  • SCD Type 0
  • SCD Type 1
  • SCD Type 2
  • SCD Type 3
  • SCD Type 4
  • SCD Type 6

8. Fact Table Types

  • Transaction fact table
  • Snapshot fact table
  • Accumulating fact table

9. Dimension Table Types

  • Conformed dimension
  • Junk dimension
  • Role playing dimension
  • Degenerate dimension

10. OLAP Concepts

  • OLAP overview
  • OLAP cube
  • Multidimensional data model
  • OLAP operations:
    • Roll-up
    • Drill-down
    • Slice
    • Dice
    • Pivot

11. Data Mart Concepts

  • What is Data Mart
  • Types of Data Mart
    • Dependent
    • Independent
    • Hybrid

12. Data Warehouse Storage and Performance

  • Indexing
  • Partitioning
  • Aggregation
  • Query optimization

13. Metadata Concepts

  • Metadata overview
  • Technical metadata
  • Business metadata

14. Data Warehouse Implementation

  • Design process
  • Development process
  • Deployment process
  • Maintenance

15. Modern Data Warehouse

  • Cloud Data Warehouse
  • Snowflake
  • Amazon Redshift
  • Google BigQuery
  • Azure Synapse

PART 2: Data Mining Syllabus List

1. Introduction to Data Mining

  • What is Data Mining
  • Data Mining vs Data Warehouse
  • Data Mining process
  • Applications of Data Mining

2. Data Preprocessing

  • Data cleaning
  • Data integration
  • Data transformation
  • Data reduction
  • Data normalization

3. Data Mining Techniques

Classification

  • Decision Tree
  • Naive Bayes
  • Logistic Regression

Regression

  • Linear Regression
  • Multiple Regression

Clustering

  • K-means clustering
  • Hierarchical clustering

Association Rule Mining

  • Apriori algorithm
  • Market basket analysis

Prediction

  • Predictive analysis

Outlier Detection

  • Anomaly detection

Sequential Pattern Mining

  • Sequence analysis

4. Evaluation and Validation

  • Accuracy
  • Precision
  • Recall
  • Confusion matrix

5. Data Mining Tools

  • Python
  • SQL
  • R
  • Power BI
  • Tableau

PART 3: SQL Topics Required for DW and DM

  • DDL
  • DML
  • Joins
  • Group By
  • Window functions
  • CTE
  • Index
  • Partition

PART 4: ETL Tools

  • SSIS
  • Azure Data Factory
  • Informatica
  • Talend

PART 5: Cloud Concepts

  • Azure
  • AWS
  • Google Cloud

Agar chaho to main next step me industry interview syllabus (sirf jo real job me use hota hai) bhi separate list de sakta hu.

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