Building Business Intelligence and Data Mining Applications - download pdf or read online

By Loria J.

- Getting details from company information- utilizing BI around the company as a vital part of doing company- seize and version your entire information- Integration with company strategies- Relational reporting and OLAP converged via a unmarried dimensional version

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Decision trees are used for classification and prediction ™ Typical questions: ™ – – – – Predict which customers will leave Help in mailing and promotion campaigns Explain reasons for a decision What are the movies young female customers likely to buy? ) Click-Stream Analysis User Sequence 1 frontpage news travel travel 2 news news news news news 3 frontpage news frontpage news frontpage 4 news news 5 frontpage news news travel travel travel 6 news weather weather weather weather 7 news health health business business business 8 frontpage sports sports sports weather 9 weather Microsoft Mining Models Association Rules ™ For – – market basket analyses Identify cross-selling opportunities Arrange attractive packages ™ Considers each attribute/value pair as an item ™ An item set is a combination of items in a single transaction ™ The algorithm scans through the dataset trying to find item sets that tend to appear in many transactions Association Rules – Support ™ Support is the percentage of rows containing the item combination compared to the total number of rows: Transaction 1: Transaction 2: Transaction 3: Transaction 4: Transaction 5: ™ Frozen pizza, cola, milk Milk, potato chips Cola, frozen pizza Milk, pretzels Cola, pretzels The support for the rule “If a customer purchases Cola, then they will purchase Frozen Pizza” is 40% Association Rules – Confidence ™ What if 60% of customers buy milk and only 20% of those buy potato chips?

Click-Stream Analysis User Sequence 1 frontpage news travel travel 2 news news news news news 3 frontpage news frontpage news frontpage 4 news news 5 frontpage news news travel travel travel 6 news weather weather weather weather 7 news health health business business business 8 frontpage sports sports sports weather 9 weather Microsoft Mining Models Association Rules ™ For – – market basket analyses Identify cross-selling opportunities Arrange attractive packages ™ Considers each attribute/value pair as an item ™ An item set is a combination of items in a single transaction ™ The algorithm scans through the dataset trying to find item sets that tend to appear in many transactions Association Rules – Support ™ Support is the percentage of rows containing the item combination compared to the total number of rows: Transaction 1: Transaction 2: Transaction 3: Transaction 4: Transaction 5: ™ Frozen pizza, cola, milk Milk, potato chips Cola, frozen pizza Milk, pretzels Cola, pretzels The support for the rule “If a customer purchases Cola, then they will purchase Frozen Pizza” is 40% Association Rules – Confidence ™ What if 60% of customers buy milk and only 20% of those buy potato chips?

Categorization ™ Semantically Measures – Dimensions – Attributes – Hierarchies – Meaningful Categories Time ™ UDM Has Built-In Knowledge of Time Natural (Calendar) – Fiscal – Reporting – Manufacturing – ISO 8601 – Translations ™ UDM provides for multiple languages ™ Metadata in BI Studio and Client Tool Displayed in Multiple Languages Attribute Semantics ™ Names Vs. ) Decision trees are used for classification and prediction ™ Typical questions: ™ – – – – Predict which customers will leave Help in mailing and promotion campaigns Explain reasons for a decision What are the movies young female customers likely to buy?

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Building Business Intelligence and Data Mining Applications with Microsoft SQL Server 2005 by Loria J.


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