1. Business Intelligence plus Enterprise Search Tuan Jean Tee Senior Project Manager, Enterprise Search Group Microsoft

2. Business Intelligence Goals & Challenges Two major goals: 1.Top line expansion 2.Bottom line performance Challenges: 1.Accuracy of data input 2.Duplication of data 3.Mixing of Structured and unstructured data 4.Scaling the performance of data storage 5.Understanding the customer’s intent and context

3. Traditional Business Intelligence Architecture Data sources Data integration using ETL Data storage Data analysis Data Presentation

4. Business Intelligence Architecture + Enterprise Search platform Enterprise Search Data sources Data integration using ETL Data storage Data analysis ReportingReporting Enterprise Search Index Search Interface Data Cleansing & enrichment

5. Business Intelligence Architecture + Enterprise Search platform Enterprise Search Data sources Data integration using ETL Data storage Data analysis ReportingReporting Enterprise Search Index Search Interface Performance scaling Information access using natural language

6. Data Cleansing & Enrichment Fuzzy Matching Data sources Data integration using ETL Data storage Linguistic Analysis Approximate Matching Data enrichment and content classification Enterprise Search Platform capabilities

7. Data Cleansing & Enrichment (2) Data cleansing using Fuzzy Matching and Linguistic Analysis Scenario: Are the following addresses the same house? Which is Suburb? Which is the City? Can you complete incomplete records? 11/17, North Sydney, NSW 2060 Unit 11, No 17, North Sydney, NSW 2060 11-17, North Syd., 2060 Level 11, 17, 2000, New South Wales, North Sydney #11-17, North Syd

8. Data Cleansing & Enrichment (3) Data cleansing using Approximate Matching Scenario: Could all of the following be the same person? Mr. Tim Smith Mr Timothy Smith T. Smith Timothy S. Tim S.

9. Data Cleansing & Enrichment (4) Data enrichment using Linguistic Analysis Scenario: What else can I derive from just the user name alone? Adam Smith Mr Jones A'shadieeyah binte Fatima

10. Data Cleansing & Enrichment (5) Data enrichment and auto-classification by linking structured data to unstructured data Content access :../category/products/sports/AFL../category/entertainment/movie Internal Blog Photos E-mails Documents External Blog Twitter Photos

11. Enterprise Search provides scalable performance platform for information access An Search Index provides alternate information access layer to the data storage This extra layer takes away the burden on data storage for data retrieval and analysis Data storage Data analysis ReportingReporting Enterprise Search Index Search Interface Performance scaling

12. Enterprise Search provides information access alternatives Enterprise Search interface provides an another channel for business user and customers to create ad-hoc queries using natural language for structured and unstructured data Enterprise Search provides relevancy model to present data in context Enterprise Search provides mechanism to slice and dice the data to discover hidden trend within the data storage Data storage Data analysis ReportingReporting Enterprise Search Index Search Interface Information Access in natural language Ad-hoc query

13. Summary Business Intelligence Architecture plus Enterprise Search gives business an improved architecture for business to expand the top line, and information to monitor bottom line performance: Enterprise Search platform provides a stacks of technologies which can supplement the traditional Business Intelligence Architecture capabilities. – Enterprise Search technologies such as linguistic analysis, fuzzy matching, approximate matching, data classification can provide a mechanism to enhance and cleanse multiple, structured data repositories into an accurate master database. – Enterprise Search technologies can link structured and unstructured data more effectively to build user profiles – Enterprise Search enable information presentation with relevancy ranking.

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