Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 30000010305814 | BF241 S73 2013 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
Go beyond design concepts and learn to build state-of-the-art visualizations
The visualization experts at Microsoft's Pragmatic Works have created a full-color, step-by-step guide to building specific types of visualizations. The book thoroughly covers the Microsoft toolset for data analysis and visualization, including Excel, and explores best practices for choosing a data visualization design, selecting tools from the Microsoft stack, and building a dynamic data visualization from start to finish. You'll examine different types of visualizations, their strengths and weaknesses, and when to use each one.
Data visualization tools unlock the stories within the data, enabling you to present it in a way that is useful for making business decisions This full-color guide introduces data visualization design concepts, then explains the various Microsoft tools used to store and display data Features a detailed discussion of various classes of visualizations, their uses, and the appropriate tools for each Includes practical implementations of various visualizations and best practices for using them Covers out-of-the-box Microsoft tools, custom-developed illustrations and implementations, and code examplesVisual Intelligence: Microsoft Tools and Techniques for Visualizing Data arms you with best practices and the knowledge to choose and build dynamic data visualizations.
Author Notes
Mark Stacey founded Pragmatic Works South Africa (a company specializing in data management and presentation) and Aphelion Software (software for visualization). He has developed visualizations for major corporations and the South African government.
Joe Salvatore is a Business Intelligence Architect with Pragmatic Works. He has been a database architect, business intelligence developer, and application developer for more than 15 years.
Adam Jorgensen is President of Pragmatic Works, Director at Large for the Professional Association of SQL Server, and a Microsoft SQL Server MVP. He regularly speaks at industry events.
Table of Contents
Introduction | p. xxiii |
Part I Introduction to Data Visualization | p. 1 |
1 Fundamentals of Visualization | p. 3 |
Data Visualization versus Artistic Visualization | p. 4 |
The Place of Infographics | p. 7 |
Using 3D Effectively | p. 7 |
The Illusion of Depth | p. 8 |
Additional Dimensions | p. 9 |
A Description of the Problem and a Proposed Solution | p. 10 |
Summary | p. 11 |
2 Designing a Visualization | p. 13 |
Goals of Visualization | p. 13 |
Human Perceptual Abilities | p. 15 |
Strategic, Tactical, and Operational Views | p. 18 |
Glance and Go versus Data Exploration | p. 21 |
Using Color in Visualizations | p. 23 |
Use of Perspective and Shape | p. 28 |
Summary | p. 31 |
Part II Microsoft's Toolset for Visualizing Data | p. 33 |
3 The Microsoft Toolset | p. 35 |
A Brief History | p. 35 |
Database Tools | p. 40 |
The Place of Each Front-End Tool | p. 44 |
Installing the Sample Databases | p. 46 |
Summary | p. 51 |
4 Building Data Sets to Support Visualization | p. 53 |
What Data Sets Are | p. 53 |
Why We Need Them | p. 53 |
How Data Sets Are Created | p. 54 |
Why Data Sets Are Important | p. 54 |
Common Data Set Elements | p. 54 |
Data Quality | p. 55 |
Metadata | p. 55 |
Formatting | p. 56 |
Data Volume | p. 56 |
Automated Data | p. 57 |
Types of Data Sets and Sources | p. 57 |
Data in the Internet Age | p. 58 |
Spreadsheets | p. 58 |
When to Store Data in a Spreadsheet | p. 58 |
SQL Tables | p. 59 |
OLAP and Tabular Models | p. 60 |
Reports and Data Feeds | p. 60 |
Hadoop and Other Nonrelational Sources | p. 61 |
Creating Data Sets for Visualization | p. 62 |
Copy and Paste | p. 62 |
Exporting Data from Systems | p. 62 |
Import Techniques and Tools | p. 62 |
Getting Started | p. 63 |
Your First Data Set | p. 63 |
Your First Data Set | p. 63 |
Getting Data | p. 64 |
Cleaning Your Data | p. 65 |
Moving Your Data into a Good Format for Visualization | p. 66 |
Verifying Your Data by Prototyping | p. 67 |
Summary | p. 68 |
5 Excel and PowerPivot | p. 69 |
What are Excel and PowerPivot? | p. 69 |
PowerPivot versus BISM versus Analysis Services | p. 69 |
Column Stores | p. 73 |
Multidimensional versus In Memory Models | p. 75 |
Creating Your First PowerPivot Model | p. 75 |
Step 1 Understand Your Data | p. 76 |
Step 2 Create Your First Model | p. 76 |
Step 3 Does Your Model Work? | p. 81 |
What Does Excel Do for Me? | p. 82 |
Pivot Charts and Tables | p. 82 |
Summary | p. 86 |
6 Power View | p. 87 |
What Is Power View? | p. 87 |
BISM: The First Requirement for Power View | p. 90 |
Creating a Power View Report | p. 91 |
Creating a Data Source | p. 91 |
Creating a New Power View Report in Excel | p. 91 |
Enhancing Data Models for Power View | p. 97 |
Cleaning Up Your Data Model | p. 97 |
Adding Metadata for Power View | p. 98 |
Sharing Power View Reports | p. 100 |
Publish in SharePoint | p. 101 |
Exporting to PowerPoint | p. 103 |
Installing the Power View Samples | p. 103 |
Summary | p. 104 |
7 PerformancePoint | p. 105 |
Tabular versus Multidimensional Sources | p. 105 |
Requirements for Running PerformancePoint | p. 106 |
SharePoint Requirements | p. 106 |
Authentication Issues when Using Secure Store Service | p. 108 |
KPIs, Scorecards, Filters, Reports, and Dashboards | p. 110 |
Creating a Data Source | p. 110 |
Mapping the Time Dimension | p. 112 |
KPIs | p. 118 |
Scorecards | p. 120 |
Filters | p. 121 |
Analytic Reports | p. 122 |
Dashboards | p. 123 |
Combining Visualizations in PerformancePoint | p. 124 |
Embedding an SSRS Report | p. 125 |
Embedding Excel Reports | p. 125 |
Creating Web Part Pages in SharePoint | p. 126 |
Adding Web Parts | p. 127 |
PerformancePoint Connections | p. 128 |
Installing the PerformancePoint Samples | p. 130 |
Summary | p. 132 |
8 Reporting Services | p. 133 |
Native versus Integrated Mode | p. 133 |
Native Mode | p. 134 |
SharePoint Integrated Mode | p. 134 |
Shared and Embedded Data Sources | p. 136 |
Authentication: A Better Solution | p. 137 |
The Double Hop Problem | p. 138 |
Set Execution Context: Requirements and Setup | p. 138 |
Expressions in Reporting Services | p. 140 |
Business Intelligence Development Studio and Visual Studio versus Report Builder | p. 141 |
Installing the Reporting Services Samples | p. 145 |
Summary | p. 146 |
9 Custom Code | p. 147 |
Silverlight, WPF, XAML, and HTML5 | p. 147 |
The Future of Silverlight | p. 150 |
Accessing Data from HTML5 | p. 151 |
Installing the HTML5 samples | p. 152 |
A Web Service Sample in C# | p. 154 |
Summary | p. 167 |
Part III Visual Analytics in Practice | p. 169 |
10 Scorecards and Indicators | p. 171 |
A Quick Understanding: Glance and Go | p. 172 |
KPIs | p. 172 |
Drill Down | p. 173 |
Drill Through | p. 174 |
Drill Across | p. 174 |
Tool Choices, with Examples | p. 175 |
PerformancePoint | p. 175 |
Excel | p. 177 |
Implementation Examples | p. 179 |
Implementing a Scorecard in Excel | p. 179 |
PerformancePoint Services (PPS) Scorecard: Traffic Lights | p. 182 |
Custom Indicators in PerformancePoint | p. 187 |
Summary | p. 189 |
11 Timelines | p. 191 |
Types of Temporal Analysis Visualization | p. 192 |
Timelines | p. 194 |
Line Charts | p. 195 |
Bar and Column Charts | p. 197 |
Combined Charting | p. 198 |
Scatter Plots and Bubble Charts | p. 799 |
Tiling | p. 200 |
Animation | p. 201 |
Tool Choices, with Examples | p. 202 |
PerformancePoint Services (PPS) | p. 202 |
SQL Server Reporting Services (SSRS) | p. 205 |
Excel | p. 208 |
Power View | p. 210 |
Implementation Examples | p. 214 |
Power View Animated Scatter Plot | p. 214 |
Combining Lines and Columns in Excel | p. 218 |
A Drillable Line Chart in PPS | p. 222 |
A Data-Driven Timeline Using SSRS and Data Bars | p. 223 |
Summary | p. 226 |
12 Comparison Visuals | p. 227 |
Overview of Point-in-Time Comparisons | p. 227 |
Explaining Perspective and Perceiving Comparisons | p. 229 |
Pie Charts Versus Bar Charts | p. 230 |
Bullet Charts | p. 231 |
Radar Charts | p. 232 |
Matrices | p. 233 |
Custom Comparisons | p. 236 |
Tool Choices, with Examples | p. 237 |
PerformancePoint Services | p. 237 |
SSRS | p. 238 |
Excel | p. 238 |
Power View | p. 240 |
HTML5 | p. 241 |
Implementation Examples | p. 242 |
PerformancePoint: Column Graphs | p. 242 |
Excel: Multiple Axes and Scale Breaks | p. 244 |
Excel: Radar Charts | p. 252 |
SSRS: A Bullet Chart | p. 254 |
HTML5 | p. 261 |
Summary | p. 267 |
13 Slice and Dice: Ad Hoc Analytics | p. 269 |
Explanation of Terms | p. 270 |
Self-Service Bl | p. 270 |
The Place of PowerPivot | p. 271 |
Definitions | p. 272 |
Tool Choices with Examples | p. 278 |
PerformancePoint: Analytic Charts | p. 278 |
PerformancePoint: Drill Across | p. 280 |
Excel Pivot Tables | p. 281 |
SSRS Drill Down and Drill Through | p. 282 |
Power View | p. 283 |
Implementation Examples | p. 284 |
SSRS: Dynamic Measures | p. 284 |
Integrating PPS and SSRS on a Single Page | p. 290 |
Power View: Exploring Data | p. 295 |
Summary | p. 298 |
14 Relationship Analysis | p. 299 |
Visualizing Relationships: Nodes, Trees, and Leaves | p. 299 |
Network Maps | p. 301 |
Color Wheel | p. 302 |
Tree Structures: Organization Charts and Other Hierarchies | p. 305 |
Strategy Maps | p. 306 |
Tool Choices | p. 307 |
PPS Decomposition Tree | p. 307 |
Excel and NodeXL | p. 308 |
PerformancePoint Services (PPS) Strategy Maps | p. 309 |
HTML5 Structure Maps | p. 310 |
Implementation Examples | p. 311 |
Building an Organization Chart in PerformancePoint | p. 311 |
Building a Network Map in HTML5 | p. 316 |
Color Wheel in HTML5 | p. 317 |
Summary | p. 320 |
15 Embedded Visualizations | p. 321 |
Tabular Data: Adding Visual Acuity | p. 322 |
Embedded Charts: Sparklines and Bars | p. 323 |
Conditional Formatting | p. 325 |
Indicators | p. 326 |
Bullet Graphs | p. 327 |
Tool Choices with Examples | p. 329 |
Excel | p. 329 |
SQL Server Reporting Services (SSRS) | p. 330 |
PerformancePoint | p. 331 |
Implementation Examples | p. 331 |
Embedding Visualizations on a Pivot Table | p. 331 |
Summary | p. 339 |
16 Other Visualizations | p. 341 |
Traditional Infographics | p. 341 |
Periodic Tables | p. 342 |
Swim Lanes | p. 344 |
Transportation Maps | p. 344 |
Mind Maps | p. 347 |
Venn Diagram | p. 347 |
CAD Drawings | p. 348 |
3D Modeling | p. 349 |
Funnels | p. 349 |
Flow Diagrams | p. 350 |
Geographic Information System Maps | p. 352 |
Heatmaps | p. 355 |
Summary | p. 355 |
A Choosing a Microsoft Tool | p. 357 |
Strengths and Weaknesses of Each Tool | p. 357 |
PerformancePoint | p. 357 |
Reporting Services | p. 358 |
Excel/Excel Services | p. 359 |
Power View | p. 360 |
HTML5 | p. 361 |
Matching a Visualization to a Tool | p. 362 |
B DAX Function Reference | p. 369 |
Date and Time Functions | p. 369 |
Filter Functions | p. 371 |
Information Functions | p. 372 |
Lookup Functions | p. 373 |
Parent-Child Functions | p. 373 |
Logical Functions | p. 374 |
Text Functions | p. 375 |
Statistical Functions | p. 378 |
Math and Trig Functions | p. 379 |
Time Intelligence Functions | p. 381 |
Index | p. 385 |