1 PERKEMBANGAN DATA WAREHOUSE FIRDAUS SOLIHIN UNIVERSITAS TRUNOJOYO Pemicu Perkembangan DW Penambahan Fungsi DW Mengadopsi Banyak Tipe Data Visualisasi Data Paralel Processing Query Tools Data Warehousing and ERP Data Warehousing and KM Web-enabled Data Warehouse
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PERKEMBANGAN DATA WAREHOUSE - FIRDAUS SOLIHIN · PERKEMBANGAN DATA WAREHOUSE FIRDAUS SOLIHIN UNIVERSITAS TRUNOJOYO PemicuPerkembanganDW PenambahanFungsiDW ... VisualisasiData Parallel
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PERKEMBANGAN
DATA WAREHOUSE
FIRDAUS SOLIHIN
UNIVERSITAS TRUNOJOYO
Pemicu Perkembangan DW
� Penambahan Fungsi DW
� Mengadopsi Banyak Tipe Data
� Visualisasi Data
� Paralel Processing
� Query Tools
� Data Warehousing and ERP
� Data Warehousing and KM
� Web-enabled Data Warehouse
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Penambahan Fungsi DW
Mengadopsi Banyak Tipe Data
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Visualisasi Data
Parallel Processing (hardware)
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Parallel Processing (Software)
� Menganalisa banyak task untukmengidentifikasi unit yang independent agar dapat di proses dalam urutan yang tepat(parallel)
� Mengidentifikasi unit2 kecil dan memastikandapat dieksekusi sesuai urutan
� Mengeksekusi unit independent dandependent sesuai urutan masing2
� Collecting, collating, dan consolidating hasilproses
Keuntungan Parallel
Processing
� Mampu menaikkan Performance dari query processing, data loading, dan index creation
� Tetap dapat digunakan walaupun adapenambahan perangkat tanpa aplikasi yang sedang dijalankan
� Tatap dapat berfugnsi walaupun beberapaperangkat paralell lain gagal bekerja
� Single logical view of the database even though the data may reside on the disks of
� multiple nodes
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Query Tools
� Flexible presentation—Easy to use and able to present results online and on reports in many different formats
� Aggregate awareness—Able to recognize the existence of summary or aggregate tables and automatically route queries to the summary tables when summarized results are desired
� Crossing subject areas—Able to cross over from one subject data mart to another automatically
Query Tools (cont)
� Multiple heterogeneous sources—Capable of accessing heterogeneous data sources on different platforms
� Integration—Integrate query tools for online queries, batch reports, and data extraction for analysis, and provide seamless interface to go from one type of output to another
� Overcoming SQL limitations—Provide SQL extensions to handle requests that cannot usually be done through standard SQL