
Explore data visualization tools and techniques, including multidimensional visualization type one and type two, and compare open source versus commercial visualization tools for data science and data analytics courses.
Explore data visualization tools and multidimensional categories. Type one covers category counts with pie, bar, histogram, and tree map; type two covers relationships with scatter plot and area chart.
Explore multi-dimensional visualization, compare open-source models with commercial tools, and examine Google charts. See how web-based visualization handles data in structured, semi-structured, or unstructured formats and creates word clouds.
Explore multidimensional visualization tools by using area, step, heat map, radar (spider), box-and-whisker, and waterfall charts, and work with Google Charts, Tableau Public, and in-memory, Hadoop-based visualizations.
Explore vertical and landscape visualization tools and how linking trace hierarchies creates interactive visuals using tools like Datawrapper, D3, Leaflet, Power BI, and Qlik.
When dealing with data sets that include hundreds of thousands or millions of data points, automating the process of data visualization makes a designer’s job significantly easier. Consuming large sets of data isn’t always straightforward. Sometimes, data sets are so large that it’s downright impossible to discern anything useful from them. That’s where data visualizations come in. Creating data visualizations is rarely straightforward. It’s not as if designers can simply take a data set with thousands of entries and create a visualization from scratch. Sure, it’s possible, but who wants to spend dozens or hundreds of hours plotting dots on a scatter chart? That’s where data visualization tools come in. Data visualization tools provide data visualization designers with an easier way to create visual representations of large data sets. When dealing with data sets that include hundreds of thousands or millions of data points, automating the process of creating a visualization, at least in part, makes a designer’s job significantly easier. These data visualizations can then be used for a variety of purposes: dashboards, annual reports, sales and marketing materials, investor slide decks, and virtually anywhere else information needs to be interpreted immediately. In this course we will be discussing various Data Visualization tools which will include Multidimentional Visualization(Type I and Type II), Multidimensional Visualization tools, Open source and commercial visualization tools. This topic is mostly a part of any course on data Science and Data Analytics.