DataMAPPER - Applied Database Tech. 이화여대 과학기술대학원 석사 3 학기 992COG08 김지혜

지식공학 -DataMAPPING 2 What is DataMAPPER? A high-performance data migration tool  Designed for large-scale data movement projects  Client-server design  Work in graphical environment without sacrificing the performance

지식공학 -DataMAPPING 3 Well balanced Client Server Architecture  Client : defining metadata, mapping relations, conversion and validation rules  Server : generating scripts in turn with client  Eliminates the network costs by executing the scripts on the server Why DataMAPPER?

지식공학 -DataMAPPING 4  DataMAPPER’s design  Project focus  Based on methodology  Stand-alone migration  Give a wider perspective over the whole migration project Why DataMAPPER?

지식공학 -DataMAPPING 5 Data Validation  Extensive data validation features  User defined additional validation rules along with the mappings  Option to drop or disable all constraints on the tables  Tremendous freedom and flexibility for moving data Why DataMAPPER?

지식공학 -DataMAPPING 6 Reusable Code Generation  DataMAPPER generates SQL*Loader, and SQL*Plus scripts which can be used outside of the tool  Used for interfacing two application systems on an on-going basis  Used for periodically loading data into a data warehouse Why DataMAPPER?

지식공학 -DataMAPPING 7 Turned for Oracle  Designed and tuned specifically for migrating into Oracle databases  Utilizes Oracle tools  Integrates with the Oracle data dictionary and recognizes the target metadata Why DataMAPPER?

지식공학 -DataMAPPING 8 Why DataMAPPER?

지식공학 -DataMAPPING 9 How It Works Define data source (metadata definition window)  View the contents of the source data files  Choose fixed or delimited text file format or use another Oracle table  Define the field attributes like data type and null constraints  Define indexes to speed up join operations or to insure uniqueness(optional)

지식공학 -DataMAPPING 10 How It Works Fig1. Define data sources

지식공학 -DataMAPPING 11 Map target tables (intuitive mapping window)  Associate target and source columns  Define conversion rules using table lookups or SQL expressions  Enter business rules as user-defined validations  Map from multiple sources  Define multiple mapping sheets for the same target table  Provide useful information about the source and target data items How It Works

지식공학 -DataMAPPING 12 How It Works Fig2. Map target tables

지식공학 -DataMAPPING 13 Generate and run scripts (script generator window)  Select table, a script type  Save and run hundreds of lines of code  Scripts are highly optimized and save automatically by dataMAPPER How It Works

지식공학 -DataMAPPING 14 How It Works Fig3. Generate and run scripts