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The section then discusses dimensional modelling, defining some salient terms: fact/measure (business numbers/amounts), dimension (descriptions), attributes (columns), fact table (facts with links to dimensions), and grain (level of fact table detail). Next, the chapter looks at building a data warehouse, emphasising its denormalized flattened tables, which improve report query performance. Finally, the Data Quality Services (DQS) component is used to maintain and improve data quality. Master Data Management (MDM) maintains the definitive version of reference data, accessible via the Master Data Services (DMS). Next, data visualization is discussed, this is what the user sees, and such tools include SQL Server Reporting Services (SSRS), Excel, and Power View. From the data warehouse, another structure is created, using SQL Server Analysis Services (SSAS), which is either file-based (OLAP cube) or memory-based (tabular model). A common ETL tool is SQL Server Integration Services (SSIS).
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Data from various source systems is extracted, transformed and loaded (ETL) into the data warehouse. The chapter continues with a look at the architecture and components of a BI system. The book opens with a look at the initial steps in creating a BI system, designing the data warehouse, which is optimized for reporting and analysis, and is used to help with decision making. So, belying its title, it is not a book for the complete beginner, some knowledge of databases and architecture, is required to get the most from the book.īelow is a chapter-by-chapter exploration of the topics covered. “.BI professionals (consultants, architects, and developers) who want to become familiar with Microsoft BI tools”. This book aims to explore Microsoft’s Business Intelligence (BI) tools and is targeted at beginners.