Konsep Aplikasi Data Mining Eka Yuniar, S.Kom., MMSI
SAP 1. Menjelaskan Definisi KDD 2. KDD Life Cycle 3. Data Warehouse 4. OLAP 5. Macam-macam OLAP 6. Arsitektur KDD 7. Arsitektur OLAP
Apa itu KDD??
Knowledge Discovery in Database Definition ”the non-trivial extraction of implicit, previously unknown and potentially useful knowledge from data” (Fall, 2003) Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. (Romi, 2010)
Mengapa Menggunakan KDD ??
Mengapa menggunakan KDD? Untuk mencari trend dan korelasi/hubungan/relation dalam data base dan dapat membantu untuk mencari informasi. Dengan tujuan : Efektif/ to more effective • menghemat waktu/ to save time • menguntungkan/to make more money • Kualitas produk/to improve product quality • to etc.
Application Marketing Market segmentation Clasification custumer Predict future sales Product Maintenance Define product interest from customer
Human Resource Management Define an employee compensation Define an employee punishment Finance Detect fraudulent use of credit cards Etc…
KDD Life Cycle
OnLine Analytical Processing (OLAP) ”the dynamic synthesis, analysis, and consolidation of large volumes of multi-dimensional data” Focuses on multi-dimensional relationships among existing data records
Olap Vs. SQL OLAP : Menambahkan Analisis dalam Tools SQL : eksekusi roll-up, drill-down, slice, dice, pivot dari DW
OLAP differs from data mining – OLAP tools provide quantitative analysis of multi-dimensional data relationships – Data mining tools create and evaluate a set of possible problem solutions (and rank them) • Ex: Propose 3 marketing strategies and order them based on marketing cost and likely sales income
Architectures for OLAP Three system architectures are used for OLAP – Relational OLAP (ROLAP) – Multi-dimensional OLAP (MOLAP) – Managed Query Environment (MQE)
ROLAP
MOLAP
MQE
Cycle of SQL
KDD Architecture
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