Data Warehousing Lecture-4
Introduction and Background
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Introduction and Background
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How is it Different?• Starts with a 6x12 availability requirement ... but
7x24 usually becomes the goal.
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Decision makers typically don’t work 24 hrs a day and 7 days a week. An ATM system does.
Once decision makers start using the DWH, and start reaping the benefits, they start liking it…
Start using the DWH more often, till want it available 100% of the time.
How is it Different?• Starts with a 6x12 availability requirement ... but
7x24 usually becomes the goal.
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For business across the globe, 50% of the world may be sleeping at any one time, but the businesses are up 100% of the time.
100% availability not a trivial task, need to take into account loading strategies, refresh rates etc.
How is it Different?• Does not follows the traditional development
model
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Classical SDLC
Requirements gathering Analysis Design Programming Testing Integration Implementation
Requirements
Program
How is it Different?• Does not follows the traditional development
model
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DWH SDLC (CLDS)
Implement warehouse Integrate data Test for biasness Program w.r.t data Design DSS system Analyze results Understand requirement
Requirements
Program
DWH
Data Warehouse Vs. OLTP
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OLTP (On Line Transaction Processing)OLTP (On Line Transaction Processing)
Select tx_date, balance from tx_tableWhere account_ID = 23876;
Data Warehouse Vs. OLTP
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DWHDWH
Select balance, age, sal, gender from customer_table, tx_tableWhere age between (30 and 40) andEducation = ‘graduate’ andCustID.customer_table = Customer_ID.tx_table;
Data Warehouse Vs. OLTP
OLTP DWH
Primary key used Primary key NOT used
No concept of Primary Index Primary index used
Few rows returned Many rows returned
May use a single table Uses multiple tables
High selectivity of query Low selectivity of query
Indexing on primary key (unique)
Indexing on primary index (non-unique)
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Data Warehouse Vs. OLTP
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Data Warehouse OLTP Scope * Application –Neutral
* Single source of “truth” * Evolves over time * How to improve business
* Application specific * Multiple databases with repetition * Off the shelf application * Runs the business
Data Perspective
* Historical, detailed data * Some summary * Lightly denormalized
* Operational data * No summary * Fully normalized
Queries * Hardly uses PK * Number of results returned in thousands
* Based on PK * Number of results returned in hundreds
Time factor * Minutes to hours * Typical availability 6x12
* Sub seconds to seconds * Typical availability 24x7
OLTP: OnLine Transaction Processing (MIS or Database System)
Comparison of Response Times• On-line analytical processing (OLAP) queries must be
executed in a small number of seconds.– Often requires denormalization and/or sampling.
• Complex query scripts and large list selections can generally be executed in a small number of minutes.
• Sophisticated clustering algorithms (e.g., data mining) can generally be executed in a small number of hours (even for hundreds of thousands of customers).
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Data Warehouse Server(Tier 1)
DataWarehouse
OperationalData Bases
SemistructuredSources Query/Reporting
Data Marts
MOLAP
ROLAP
Clients(Tier 3)
Tools
MetaData
Data sources
Data(Tier 0)
IT
Users
BusinessUsers
Business Users
Data Mining
Archiveddata
Analysis
OLAP Servers(Tier 2)
ExtractTransformLoad (ETL)
www data
Putting the pieces togetherPutting the pieces together
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