Visualizing Graph Data
Visualizing Graph Data
ways in which each datum-person, product, etc-connects to another.
Visualizing these graphs makes it possible to literally see the
connections. The graph model consists of data elements, called nodes,
and edges, which are the relationships between these nodes. Graphs
make the relationships between the data elements a core part of the
data structure, which means you can better comprehend the meaning of
your data. And visual data is easier for everyone to understand.
Visualizing Graph Data teaches readers not only how to build graph
data structures, but also how to create their own dynamic, interactive
visualizations using a variety of tools. This book is loaded with
fascinating examples and case studies to show the real-world value of
graph visualizations. It begins by teaching fundamental graph concepts
and techniques used to visualize graph data. Next, readers drill down to
learn how to create their own useful visualizations, as well as
additional tools. Readers also learn how to model data, create the best
graphs for their particular audience, handle big data, and depict
temporal and spatial data. By the end of this book, readers know to ask
the right questions of data to create powerful visualizations.
Key Features:
* Real-world case studies
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ways in which each datum-person, product, etc-connects to another.
Visualizing these graphs makes it possible to literally see the
connections. The graph model consists of data elements, called nodes,
and edges, which are the relationships between these nodes. Graphs
make the relationships between the data elements a core part of the
data structure, which means you can better comprehend the meaning of
your data. And visual data is easier for everyone to understand.
Visualizing Graph Data teaches readers not only how to build graph
data structures, but also how to create their own dynamic, interactive
visualizations using a variety of tools. This book is loaded with
fascinating examples and case studies to show the real-world value of
graph visualizations. It begins by teaching fundamental graph concepts
and techniques used to visualize graph data. Next, readers drill down to
learn how to create their own useful visualizations, as well as
additional tools. Readers also learn how to model data, create the best
graphs for their particular audience, handle big data, and depict
temporal and spatial data. By the end of this book, readers know to ask
the right questions of data to create powerful visualizations.
Key Features:
* Real-world case studies
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