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Navigating Business Intelligence: Insights and Strategies by Jose Chinchilla

Join Jose Chinchilla, an expert in Business Intelligence and Database Administration, for a comprehensive overview of the BI landscape. This session covers essential concepts like ETL, data warehousing, and decision support systems. Explore the Microsoft Toolset for BI, learn about the Business Intelligence roadmap, and understand the maturity stages crucial for effective implementation. Gain practical knowledge through demos of SSIS, SSAS, and SSRS, and benefit from top rules of wisdom for BI success. Enhance your decision-making capabilities and empower your organization with actionable insights.

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Navigating Business Intelligence: Insights and Strategies by Jose Chinchilla

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Presentation Transcript

  1. MicrosoftBusiness Intelligence Presented by: Jose Chinchilla, MCITP

  2. Jose Chinchilla MCITP: Database Administrator, SQL Server 2008 MCITP: Business Intelligence Design and Implementation, SQL Server 2008 President & CEO, Agile Bay, Inc. President, Tampa Bay Business Intelligence User Group “DBA by accident, BI Developer by chance, Geek by Choice” Blog: http://www.sqljoe.com Twitter: http://www.twitter.com/sqljoe Linked-in: http://www.linkedin.com/in/josechinchilla Email: jchinchilla@sqljoe.com jchinchilla@agilebay.com

  3. Agenda • Terms and Acronyms • Business Intelligence & Data Warehouse • Lifecycle for Decision Support Systems • BI & DW Define • ETL, Analysis, & Presentation Layers • Microsoft Toolset for BI & DW • The Business Intelligence Roadmap: • How to start the Business Intelligence journey? • The Business Intelligence Maturity Stages • Top 5 rules of wisdom for Business Intelligence success • Demo: SSIS, SSAS, SSRS, PowerPivot • Q&A

  4. Terms & Acronyms BI: Business Intelligence ETL: Extract, Transform & Load DW: Data Warehouse KPI: Key Performance Indicator Fact: A business measurement Measure: A quantifiable business process Dimension: Breakdown measures according to an area of interest Attribute: Characteristics that makeup a dimension member OLTP: On-Line Transactional Processing OLAP: On-Line Analytical Processing Cube: Data structure that groups measures, dimensions, KPIs, data mining models, perspectives Metadata: Data about data Granularity: Level of detail or summarization of the data SCD: Slowly Changing Dimensions Alternate Key: Unique key from data source Surrogate Key: Unique key in the data warehouse

  5. Typical Business Intelligence Lifecycle

  6. What is Business Intelligence ?

  7. “BI results when organizational culture, business processes and technologies are designed and implemented with the goal of improving the strategic and operational decision-making capabilities of a wide range of internal and external stakeholders.” - International Data Corporation (IDC

  8. “BI results when organizational culture, businessprocessesandtechnologiesare designed and implemented with the goal of improving the strategic and operational decision-makingcapabilities of a wide range of internal and external stakeholders.” - International Data Corporation (IDC

  9. Culture, processes and technologies to improve decision making for stakeholders.

  10. What Business Intelligence is not !

  11. What it is not… What it is… • Application • Tool • Department • Project • Report Base • Archive • IT Service • Solution • Suite • Interdepartmental Team • Continuous process • Knowledge Base • Actionable Information • Business Asset

  12. The Data Warehouse

  13. A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. - Bill Inmon

  14. A data warehouse is a central repository for all or significantparts of the datathat an enterprise'svarious business systems collect. - Bill Inmon

  15. Data Warehouse: central repository for all significant data that an enterprise collects

  16. Small OLTP database

  17. Business Issue: A customer’s order was seriously delayed. Manager: Why? Order Fulfillment: Supplier issue. Simple Business Question: Who was our product supplier?

  18. 1 4 3 2 Small OLTP database

  19. 33 5 11 7 1 3 10 8 42 89 2 6 9 12 4 28 Large OLTP database

  20. Manager: Where’s my data? DBA: Query still running.

  21. Ralph Kimball Bill Inmon Vs. Star Schema Snowflake Schema Data Warehouse: Data Model

  22. Star Schema

  23. 1 to Many

  24. 1 to Many to Many Data Model: Snowflake Schema

  25. The OLAP Cube

  26. Measure: Units sold Dimension: Product Dimension: Geography Dimension: Time Fact:37 Lemons were sold during April in our Chicago stores.

  27. 3 Layers of BI & The Microsoft Toolset

  28. One or many data sources • One or many data marts • One or many uses Data Warehouse: ETL

  29. The Microsoft Toolset

  30. How to start? Where to start?

  31. BI Maturity Stages * Information Management

  32. Right Presentation to Right Audience

  33. 5 Rules of BI Wisdom for Success

  34. Who is your sponsor?

  35. Technology adequate for the skillsets? Skillsets adequate for the technology?

  36. Tool? Tool Features? Content! What makes BI successful?

  37. Bobby, where’s my !@$%& report ? Are empowering users ?

  38. Consultant Are you missing any part of the puzzle?

  39. Demo: SSIS SSAS PowerPivot SSRS

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