12. Visual Analytics:
-beyond numbers, static graphs and charts
Use interactive visual interface
See the overview
Find pattern, trend, outlier, correlation
Sort by rank, group similar things
Make decision or ask more questions
18. Tools
MicrosStrategy
Tableau
SpotFire
ManyEyes
NodeXL
Gephi
D3: JavaScript library
Commercial tool for
Business data analysis
19. Information Visualization Mantra
Ben Shneiderman
Overview: see the big picture
Zoom and Filter: select only relevant data
Details on Demand: gain more details of the
selected data point
37. Challenge of Big Data Visualization
Performance
Understand the data
Meaningful grouping
Context
Data quality
Detecting outliers
Consolidating various data sources
Various platforms
38. Census:
https://www.census.gov/dataviz/
Census for STEM:
http://www.census.gov/dataviz/visualizations/stem/stem-html/
NY times:
http://www.nytimes.com/upshot/ Mostly analysis, but they also provide interactive viz
http://www.nytimes.com/interactive/2014/upshot/mapping-the-spread-of-drought-across-the-
us.html
Blogs:
http://datastori.es/
http://fellinlovewithdata.com/
Visualcomplexity
Flowing Data: http://flowingdata.com/
http://www.visualizing.org/
http://www.tableausoftware.com/public/gallery
List of tools: http://selection.datavisualization.ch/
Twitter visualizations: http://twitter.github.io/interactive/newyear2014/
Simple statistical properties failed to convey the actual overview. May be there is some outlier. Or trend, pattern.
Stock price of companies : https://www.google.com/finance?chdnp=1&chdd=1&chds=1&chdv=1&chvs=maximized&chdeh=0&chfdeh=0&chdet=1419314117233&chddm=50048&chls=IntervalBasedLine&cmpto=NASDAQ%3AAAPL%3BNASDAQ%3AYHOO%3BNASDAQ%3AMSFT&cmptdms=0%3B0%3B0&q=NASDAQ%3AGOOGL&ntsp=0&fct=big&ei=oQOZVPmlEOjtsQfi_YGIAg
Combination of map data and network data
http://www.visualcomplexity.com/
D3
Dashboards
a computer-driven transformation of abstract data into an interactive visual depiction aiming at insight – which in turn translates into “discovery, decision-making, and explanation”
Manuel Lima
Which sequence you want to present the data viz to the analysts, who are the users, what is their questoins
Ben Shneiderman: Information Visualization Mantra
Anything you will do with data, you should aim to do visually, and meaningfully.
More and more interaction come in the last two stages
Now you want to know: why? Who rated the movie? Are they like you? You want to drill more into this.
Not only the average rating, you also see the distribution of the rating.