Welcome introduction
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The document discusses challenges and solutions related to business intelligence (BI) and data management in enterprises, emphasizing the need for agility, consistency, and alignment with business goals. It outlines the importance of understanding current environments and implementing effective information architecture through various schema designs. Additionally, it highlights a transition from a less efficient architecture to a more structured one for improved BI effectiveness.
Welcome introduction
- 3. ARE YOU ABLE TO… … react quickly to changes in competition, regulation and customer/stakeholder demands? … guarantee consistency and accuracy of reports with data defined differently throughout your enterprise? … keep business goals and business intelligence implementations in lock step? … demonstrate to management the value of business intelligence investments? © 2011 SAP AG. All rights reserved. 3
- 4. DO YOU HAVE…. … a Clear Understanding of Your Current Environment? … Agility to Respond Quickly to Changes in Business & IT? … Methods to Streamline Development & Deployment? © 2011 SAP AG. All rights reserved. 4
- 5. BI EXPERTS HAVE BEEN KEEP SAYıNG.... 1 2 3 © 2011 SAP AG. All rights reserved. 5
- 6. Go From This for Your EA © 2011 SAP AG. All rights reserved. 6
- 7. To This For information Architecture Recommended architecture - example © 2011 SAP AG. All rights reserved. 7
- 8. To This for Business © 2011 SAP AG. All rights reserved. 8
- 9. To This for Applications © 2011 SAP AG. All rights reserved. 9
- 10. To This for Technology © 2011 SAP AG. All rights reserved. 10
- 11. To This For Database Warehouse Design • Star schema Location Product Location ID integer <pk> Time Country varchar(30) Time ID integer <pk> Product ID integer <pk> City varchar(30) Year integer Name varchar(30) Month integer Day integer Sales Sales ID integer <pk> Product ID integer <fk1> Location ID integer <fk2> ... Country Country ID integer <pk> Country Name varchar(30) City • Snowflake schema Product Category City ID integer <pk> Month Category ID integer <pk> Country ID integer <fk> Month Number integer <pk> Category Name varchar(30) City Name varchar(30) Month Name varchar(10) Zip varchar(30) Location Time Product Location ID integer <pk> Product ID integer <pk> Time ID integer <pk> City ID integer <fk> Category ID integer <fk> Month Number integer <fk> Name varchar(30) Year integer Month integer Day integer Sales Sales ID integer <pk> Product ID integer <fk1> Location ID integer <fk2> ... Country_City_Location Country ID <h:1> Country Name City ID <h:2> City Name Zip Location ID <h:3> Hierarchy_1 <Default> <h> Multi-Dimensional schema Sales - Country_City_Location Month_Time Month Number <h:1> Sales Month Name Sales - Month_Time Time ID <h:2> Sales ID Sales number Year Month Sales Day Hierarchy_1 <Default> <h> Sales - Product Category_Product Product Category_Product Category ID <h:1> Category Name Product ID <h:2> Name Hierarchy_1 <Default> <h> © 2011 SAP AG. All rights reserved. 11
- 13. Thank You! Muzaffer YÖNTEM | Sales Business Development Director Sybase Turkey muzaffer.yontem@sybase.com.tr www.sybase.com.tr