data warehouse

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Presentation Transcript

Data Warehousing : 

Data Warehousing

Warehousing : 

Warehousing Growing industry: $8 billion in 1998 Range from desktop to huge: Walmart: 900-CPU, 2,700 disk, 23TBTeradata system Lots of buzzwords, hype slice & dice, rollup, MOLAP, pivot, ... 2

Outline : 

Outline What is a data warehouse? Why a warehouse? Models & operations Implementing a warehouse Future directions 3

What is a Warehouse? : 

What is a Warehouse? Collection of diverse data subject oriented aimed at executive, decision maker often a copy of operational data with value-added data (e.g., summaries, history) integrated time-varying non-volatile 4

What is a Warehouse? : 

What is a Warehouse? Collection of tools gathering data cleansing, integrating, ... querying, reporting, analysis data mining monitoring, administering warehouse 5

Warehouse Architecture : 

Warehouse Architecture 6 Metadata

Why a Warehouse? : 

Why a Warehouse? Two Approaches: Query-Driven (Lazy) Warehouse (Eager) 7

Query-Driven Approach : 

Query-Driven Approach 8

Advantages of Warehousing : 

Advantages of Warehousing High query performance Queries not visible outside warehouse Local processing at sources unaffected Can operate when sources unavailable Can query data not stored in a DBMS Extra information at warehouse Modify, summarize (store aggregates) Add historical information 9

Advantages of Query-Driven : 

Advantages of Query-Driven No need to copy data less storage no need to purchase data More up-to-date data Query needs can be unknown Only query interface needed at sources May be less draining on sources 10

OLTP vs. OLAP : 

OLTP vs. OLAP OLTP: On Line Transaction Processing Describes processing at operational sites OLAP: On Line Analytical Processing Describes processing at warehouse 11

OLTP vs. OLAP : 

OLTP vs. OLAP Mostly updates Many small transactions Mb-Tb of data Raw data Clerical users Up-to-date data Consistency, recoverability critical Mostly reads Queries long, complex Gb-Tb of data Summarized, consolidated data Decision-makers, analysts as users 12 OLTP OLAP

Data Marts : 

Data Marts Smaller warehouses Spans part of organization e.g., marketing (customers, products, sales) Do not require enterprise-wide consensus but long term integration problems? 13