Applied microsoft business intelligence / / Patrick LeBlanc [and three others]

• Record Nr.: UNINA9910131265603321
• Autore: Leblanc Patrick
• Pubbl/distr/stampa: Indianapolis, Indiana : , : Wiley, , 2015; ©2015
• ISBN: 1-118-96178-1; 1-118-96179-X
• Edizione: [1st edition]
• Descrizione fisica: 1 online resource (432 p.)
• Disciplina: 658.47028
• Soggetti: Business intelligence - Computer programs; Business planning
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Nota di contenuto: Cover; Title Page; Copyright; Contents; Introduction; Part I Overview of the Microsoft Business Intelligence Toolset; Chapter 1 Which Analysis and Reporting Tools Do You Need?; Selecting a SQL Server Database Engine; Building a Data Warehouse; Selecting an RDBMS; Selecting SQL Server Analysis Services; Working with SQL Server Reporting Services; Understanding Operational Reports; Understanding Ad Hoc Reporting; Working with SharePoint; Working with Performance Point; Using Excel for Business Intelligence; What Is Power Query?; What Is Power Pivot?; What Is Power View?; Power Map; Which Development Tools Do You Need?Using SQL Server Data Tools; Using SQL Management Studio; Using Dashboard Designer; Using Report Builder; Summary; Chapter 2 Designing an Effective Business Intelligence Architecture; Identifying the Audience and Goal of the Business Intelligence Solution; Who's the Audience?; What Is the Goal(s)?; What Are the Data Sources?; Using Internal Data Sources; Using External Data Sources; Using a Data Warehouse (or Not); Implementing and Enforcing Data Governance; Planning an Analytical Model; Planning the Business Intelligence Delivery Solution; Considering Performance Considering Availability; Summary; Chapter 3 Selecting the Data Architecture that Fits Your Organization; Why Is Data Architecture Selection Important?; Challenges; Benefits; How Do You ; Pick the Right Data Architecture?; Understanding Architecture Options; Understanding Research Selection Factors; Interviewing Key Stakeholders; Completing the Selection Form; Finalizing and Approving the Architecture; Summary; Part II Business Intelligence for Analysis; Chapter 4 Searching and Combining Data with Power Query; Downloading and Installing Power Query; Importing Data; Importing from a Database Importing from the Web; Importing from a File; Transforming Data; Combining Data from Multiple Sources; Splitting Data; Aggregating Data; Introducing M Programming; A Glance at the M Language; Adding and Removing Columns Using M; Summary; Chapter 5 Choosing the Right Business Intelligence Semantic Model; Understanding the Business Intelligence Semantic Model Architecture; Understanding the Data Access Layer; Using Power Pivot; Using the Multidimensional Model; Using the Tabular Model; Implementing Query Languages and the Business Logic Layer; Data Analytics Expressions (DAX)Multidimensional Expressions (MDX); Direct Query and ROLAP; Data Model Layer; Comparing the Different Types of Models; Which Model Fits Your Organization?; Departmental; Team; Organizational; Summary; Chapter 6 Discovering and Analyzing Data with Power Pivot; Understanding Hardware and Software Requirements; Enabling Power Pivot; Designing an Optimal Power Pivot Model; Importing Only What You Need; Understanding Why Data Types Matter; Working with Columns or DAX Calculated Measures; Optimizing the Power Pivot Model for Reporting; Understanding Power Pivot Model Basics
• Sommario/riassunto: Leverage the integration of SQL Server and Office for more effective BI Applied Microsoft Business Intelligence shows you how to leverage the complete set of Microsoft tools-including Microsoft Office and SQL Server-to better analyze business data. This book provides best practices for building complete BI solutions using the full Microsoft toolset. You will learn how to effectively use SQL Server Analysis and Reporting Services, along with Excel, SharePoint, and other tools to provide effective and cohesive solutions for the enterprise. Coverage includes BI architecture, data queries