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Learning Path Big Data Visualization

Learning Path Big Data Visualization
Last updated 8/2017
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 691.10 MB | Duration: 5h 1m
Gain hands-on experience in creating effective visualizations of your data


What you'll learn
Find out how to utilize visualization best practices
Discover how to identify and understand your source data
Get to know how to match your dataset to the appropriate visualization type
See how to optimize basic chart types for maximum impact
Understand, validate, and optimize your data for effective visualizations
Find out the best ways to maximize the impact of basic chart types
Get to know to optimize map displays
Create, build, and optimize network graphs using connected data
Requirements
Basic knowledge of HTML, CSS, and jаvascript would be helpful, but is not manadatory
Some experience with database, spreadsheet, and presentation software will be beneficial
Description
Data visualization is becoming critical in today's world of Big Data. If you are a data analyst or a Big Data enthusiast and want to explore the various techniques of data visualization, then this Learning Path is for you! This Learning Path focus on building a variety of data visualizations using multiple tools and techniques!
Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. The highlights of this Learning Path are
Learn why data visualization is important, and how it can be used to manage Big Data Learn best practices in data visualization and apply them to your own displays
Let's take a quick look at your learning journey. To start with, we will walk you through an overview of the basic principles of data visualization, why they are important, and how they can be used to make visualizations highly effective. We will then walk you through some of the basics such as how to build visualizations using best practices. You'll also learn how to identify data types and match them with the appropriate display formats.Then, we will focus on building a variety of data visualizations using multiple tools and techniques. This is where we will put the theory together with actual hands-on experience of creating effective visualizations. Our efforts will be spent on choosing the best display types for our dataset, and then applying best practice principles to our selected charts, maps, or network graphs. We will spend considerable time on some of the most useful chart types, followed by a section where we explore the multiple uses of maps as visualizations. Finally, we will focus on understanding network graphs, a powerful tool for displaying relationship data.
By the end of this Learning Path, you will have a strong understanding of how to effectively visualize your data.
About the Author
Ken Cherven has been creating data visualizations for more than 10 years using a variety of tools, including Excel, Tableau, Cognos, D3, Gephi, Sigma.js, and Exhibit, along with geospatial tools such as Mapbox, Carto, and QGIS. He has built many visualizations for his personal websites, especially utilizing Gephi and Sigma.js to explore and visualize network data. His experience in building data visualizations has intersected with many technologies, including a variety of SQL-based tools and languages including Oracle, MySQL, and SQLServer. His work is based on a thorough understanding of visualization principles learned through extensive reading and practice. He also uses his websites to display and promote visualizations, which he shares with a wider audience. He has previously authored two books on Gephi for Packt, and has also presented at multiple data visualization conferences.
Overview
Section 1: Learning Data Visualization
Lecture 1 The Course Overview
Lecture 2 Visualizing Is Critical to Understanding
Lecture 3 Taming Big Data through Visualization
Lecture 4 Utilizing Visualization Tools
Lecture 5 Introducing Visualization Best Practices
Lecture 6 Designing for Visual Clarity
Lecture 7 Driving User Focus
Lecture 8 Working with Element Sizing
Lecture 9 Employing Color Effectively
Lecture 10 Data Types Overview
Lecture 11 Categorical Data
Lecture 12 Time Series Data
Lecture 13 Point (X-Y) Data
Lecture 14 Geospatial Data
Lecture 15 Network Data
Lecture 16 Unstructured Data
Lecture 17 Line Charts
Lecture 18 Bar Charts
Lecture 19 Scatter Plots
Lecture 20 Distribution Plots
Lecture 21 Dot Plots
Section 2: Data Visualization Techniques
Lecture 22 The Course Overview
Lecture 23 Understanding the Data
Lecture 24 Preparing the Data
Lecture 25 Validating the Data
Lecture 26 Selecting the Best Display Option
Lecture 27 Creating Effective Line Charts
Lecture 28 Building Powerful Bar Charts
Lecture 29 Designing Effective Dot Plots
Lecture 30 Building Distribution Plots
Lecture 31 Creating Effective Scatterplots
Lecture 32 Working with Box Plots
Lecture 33 Mastering Bullet Graphs
Lecture 34 Understanding Your Map Data
Lecture 35 Building Dot Density Maps
Lecture 36 Creating Categorical Maps
Lecture 37 Designing Choropleth Maps
Lecture 38 Enhancing Your Map
Lecture 39 Sharing a Map
Lecture 40 Creating and Procuring Network Data
Lecture 41 Building a Network Graph
Lecture 42 Understanding Graph Metrics
Lecture 43 Styling the Graph by Sizing Elements
Lecture 44 Styling the Graph Using Color
Lecture 45 Sharing the Graph
This Learning path is for data analysts and data enthusiasts who are looking to learn what is data visualization and its different techniques.


Homepage
https://www.udemy.com/course/learning-path-big-data-visualization/






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