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Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide

By : Abolfazl Radgoudarzi, Reza Rad
Book Image

Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide

By: Abolfazl Radgoudarzi, Reza Rad

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Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide
Abolfazl Radgoudarzi | Reza Rad
May, 2014 | 350 pages
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Table of Contents (19 chapters)
Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide
Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Data Warehouse Design
Data Warehouse Design
Understanding Business Intelligence
The architecture and components of a BI system
Building the data warehouse
Summary
2
SQL Server Analysis Services Multidimensional Cube Development
SQL Server Analysis Services Multidimensional Cube Development
Why is OLAP required?
Understanding the SQL Server Analysis Services engine
Developing your first cube
Time for action – creating an Analysis Services project
Time for action – creating the first cube
Time for action – viewing the cube in the browser
Dimensions and measures
Time for action – using the Dimension Designer
Time for action – change the order of the Month attribute
Time for action – modifying the measure properties
Data Source View
Time for action – creating a Named Calculation
Time for action – using a Named Query
Using dimensions
Time for action – adding a Fact relationship
Hierarchies
Time for action – creating a hierarchy
Multidimensional eXpression, calculated members, and Named Sets
Time for action – writing an MDX query
Time for action – calculated members
Deploying and processing
Time for action – deploying an SSAS project
Time for action – processing the data
Summary
3
Tabular Model Development of SQL Server Analysis Services
Tabular Model Development of SQL Server Analysis Services
Introducing SSAS Tabular
Developing a tabular project
Time for action – creating a tabular project
Time for action – creating measures
Creating hierarchies
Time for action – creating a hierarchy from a single table
Time for action – creating a hierarchy from multiple tables
Data Analysis eXpression, calculated columns, and measures
Time for action – using time intelligence functions in DAX
Securing the data
Time for action – security in tabular
Storage modes
Time for action – creating a model with the DirectQuery storage mode
Tabular versus Multidimensional SSAS
Summary
4
ETL with Integration Services
ETL with Integration Services
Understanding ETL and data consolidation
SQL Server Integration Services
Integration Service projects and packages
Time for action – creating your first SSIS project
The Control Flow tab
Time for action – working with Control Flow tasks
The Data Flow tab
Time for action – loading customer information from a flat file into a database table with a Data Flow Task
Containers and dynamic packages
Time for action – looping through CSV files in a directory and loading them into a database table
Deploying and executing
Time for action – deploying an SSIS project
Time for action – executing an SSIS package from a catalog
Summary
5
Master Data Management
Master Data Management
Understanding Master Data Management
Master Data Services
Time for action – configuring MDS
Comparing WebUI with the Excel Add-in
Time for action – installing Excel Add-in
Creating models and entities
Time for action – creating a model and an entity
Time for action – creating an entity with data from the Excel Add-in
Time for action – change tracking
The entity relationship
Time for action – creating a domain-based relationship
Business rules
Time for action – creating a simple business rule
Working with hierarchies
Time for action – creating a derived hierarchy
Security and permission
Time for action – permission walkthrough
Integration management
Time for action – a subscription view
Time for action – entity-based staging
Summary
6
Data Quality and Data Cleansing
Data Quality and Data Cleansing
Understanding data quality
Data Quality Services
Time for action – installing Data Quality Services
Knowledge Base Management
Time for action – creating a Knowledge Base
Knowledge discovery
Time for action – knowledge discovery
Data cleansing with Data Quality Projects
Time for action – using Data Quality Project for cleansing
Domain and composite domain rules
Time for action – composite domain rules
Synonyms and standardization
Time for action – creating synonyms and setting standardization
Matching
Time for action – matching policy
Time for action – matching projects
Integrating with MDS and SSIS
Time for action – the DQS cleansing component in SSIS
Summary
7
Data Mining – Descriptive Models in SSAS
Data Mining – Descriptive Models in SSAS
An introduction to data mining
The Microsoft Decision Tree algorithm
Time for action – creating a data mining solution with the Microsoft Decision Tree algorithm
Microsoft association rules
Time for action – the Microsoft association rule
Summary
8
Identifying Data Patterns – Predictive Models in SSAS
Identifying Data Patterns – Predictive Models in SSAS
Finding the best algorithm
Time for action – finding the best mining model with Lift Chart and Profit Chart
Predicting data with DMX
Time for action – predicting prospective bike buyers
Microsoft Time Series
Time for action – predicting future sales with Microsoft Time Series
Summary
9
Reporting Services
Reporting Services
The Reporting Services architecture
Developing a basic report
Time for action – creating our first report using SSRS
Extended report development
Time for action – adding parameters to a report
Printing and page configuration
Time for action – changing a page's properties
Sorting and grouping
Time for action – applying ordering and grouping on the data rows
Expressions
Time for action – changing the background color of data rows based on expressions
Time for action – working with charts in Reporting Services
Deploying and configuring
Time for action – deploying a report
Time for action – using Report Manager
Summary
10
Dashboard Design
Dashboard Design
The PerformancePoint service
Time for action – configuring PerformancePoint in SharePoint
Time for action – creating your first dashboard with PerformancePoint Dashboard Designer
Time for action – creating a dashboard page
Time for action – exploring on-the-fly features
Time for action – working with filters
Power View
Time for action – enabling Power View in Excel
Time for action – creating the first Power View dashboard
Time for action – geographical data visualization using Power View
Time for action – visualizing time-based information with a scatter chart
Time for action – using Filter in Power View
Summary
11
Power BI
Power BI
Self-service ETL with Power Query
Time for action – self-service ETL with Power Query
Power Map
Time for action – data visualization with Power Map
Summary
12
Integrating Reports in Applications
Integrating Reports in Applications
Designing .NET applications with reports
Time for action – installing AdventureWorks SSRS sample reports
Developing reports in a web application
Time for action – working with reports in web/Windows applications
Developing reports in a Metro application
Time for action – working with reports in Metro applications
Working with ReportViewer in a local processing mode
Time for action – designing reports and working with the local processing mode
Passing parameters to a report
Time for action – changing a report configuration with a ReportViewer Object through code behind
Using the results of a mining model in an application
Time for action – running DMX queries from a .NET application
Summary
Index
Index

Data cleansing with Data Quality Projects

Knowledge Bases are created for one main reason—cleaning data. Data Quality Projects (DQPs) are created for the same reason. Each DQP works with one Knowledge Base. It gets data from a source file or SQL Server database and applies the Knowledge Base on it. Then, the result of DQP can be exported to the database tables or files.

In this section, you will see how to create data quality projects to cleanse data. There is also another type of DQP for data matching, which will be discussed later in this chapter.

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