MKTG 404 Exam 1 - FLASHCARDS - 3_ Tools to visualize data and visualization pt 2
What are examples of different data visualization tools?
Excel
Google charts
Power BI
Tableau
Geospatial visualization tools
What are different programming tools?
R programming
Javascript
Python
What are the pros of Excel?
- Supports processing of data
- Compatible with Word and Power Point
- Relatively easy to learn
- Widely used
What are the cons of Excel?
- Good for basic visualization - not interactive
- Require customization to adhere to design standards
- May not process large dataset (~1GB)
What are the pros of Google Charts?
- Free and open option to create charts
- Include interactive, animated, and geospatial data graphics
- Integrates well with Google Apps Suite (such as Google Docs)
- Can easily access data from different computers
What are the cons of Google Charts?
- Requires customization to adhere to design standards
- May not be effective to process very large datasets (approaching ~1GB)
What are the pros of Power BI?
- Tightly integrated with other Microsoft tools – Excel, Azure Cloud Service, SQL Server
- Highly intuitive user interface
- Affordable
- Robust built in library of visuals
- Can import data from a wide range of sources
What are the cons of Power BI?
- Not many options to configure and optimize your visuals
- May not handle several relationships between tables well
- May have performance issues when importing large datasets
What are the pros of Tableau?
- Designed to explore and analyze data visually
- Integrate a wide range of data sources and file types
- Careful thought given to design and aesthetics - Inspired by the Grammar of Graphics
- Allows for interactive, spatial, animated, and dashboard displays
- Powerful community collaboration
What are the cons of Tableau?
- Initial data preparation required, recently Tableau has launched Tableau prep, a separate software to prep data
- Expensive
- In the free Public version, any data you upload to the servers becomes publicly available
What are the pros of R programming?
- Free open-source statistical programming language
- Built and maintained for statisticians by statisticians
- Capable of both data analysis and data graphics
- Libraries used for visualization in R: Graphics, ggplot2, car, lattice, ndtv, plotly
- Can write your own functions and packages to make graphics the way you want
What are the cons of R programming?
- Default chart outputs require design refinements: Lack of titles, Undefined scales for axes
- Use R to create graphs and edit and refine using design software: Adobe Illustrator, Inkmap
- R is great for exploratory data visualization (analysis) but may not be the best tool for explanatory data visualization (presenting results and storytelling)
What are the pros of Python?
- Can handle large amounts of data without crashing
- Useful for analyses and heavy computation
- Clean and easy-to-read syntax
- Some of Python’s data visualization libraries: Matplotlib, seaborn, geoplotlib, ggplot
True or false: a con of Python is that it is a great starting point for data exploration, not very good aesthetically?
TRUE
What are the pros of Javascript?
- Web-based scripting language
- Some JavaScript libraries – D3, rCharts, HighCharts, charts.js, dimple.js
- Freely available and allow users to create sophisticated web-based visualizations
What are the cons of Javascript?
- Steep learning curve
- Require skills in working with HTML and JSON
True or false: There is no one-size-fits all solution to visualizing data?
TRUE