Synopsis
1. Data Visualization - Concept
● Data visualization principles and values
● Communicate data driven findings
● Machine learning and data visualization
● Inference and Modeling in data visualization
● Informative datasets and software for reliance data visualization
2. Data Visualization Techniques
● Improving decision-making skills by boosting visual thinking
● Understanding how people interpret different types of visual information
● Using a wide array of graphs and charts to understand, analyze, and refine data
● Working with multidimensional data and mapping it to graphical elements
● Effective Space Usage , Mapping & Cartography
● Leveraging data visualization and design principles to connect with your audience
3. Data Visualization Tools
● Building better visualization tools and systems● Practical approach of building and evaluating visualization systems
● Data visualization graphics API
● Information visualization and information graphics
● communicating, understanding, and analyzing data
4. Data Visualization for Big Data Technologies● Big data visualization principles
● Process multiple types of incoming data
● Enabling big data analysis visualization in real time
● Single, two and multidimensional big data visualization
● Big data visualizing patterns or on visualizing details
5. Applications of Data Visualizations
● Data visualization for in-house communication and client reporting
● Marketing content and data visualization
● Collaborative Visual Analysis
● Text and Narrative Visualization
"synopsis" may belong to another edition of this title.
