Choosing a data visualization tool is like being a barista serving coffee: everyone wants their data, their way, personalized, fast, and perfect. Many organizations have a cottage industry of data visualization tools, and it's difficult to know what tool to use, and when. Different tools exist in different departments, and if it doesn't meet the user requirements, the default position is to go back to Excel and move the data around there. This session will examine data visualization tools such as SSRS Excel, Tableau, QlikView, Datazen, Kibana and PowerBI, in order to craft and blend your data visualization tools to serve your data customers better.

1. Datavis Barista: How to choose what
dataviz tool, and when
Jen Stirrup
Founder, Data Relish
Level: Intermediate

2. Who am I? Jen Stirrup

3. What dataviz tool to choose, and
when?
• SSRS
• Excel
• Tableau
• Power BI
• Datazen
• Kibana

4. What makes a good Visualisation?
• Effective
• Accurate
• Efficient
• Aesthetics
• Adaptable

9. https://www.quora.com/What-are-the-worst-infographics-youve-ever-seen

12. http://www.designyourway.net/blog/inspiration/when-infographics-go-
bad-or-how-not-to-design-data-visualization/

14. What makes a good Visualisation?
• Effective
• Accurate
• Efficient
• Aesthetics
• Adaptable

15. Excel, Datazen, SSRS, Power BI

16. SQL Server 2016

17. SQL Server 2016

18. SQL Server 2016

19. Datazen

20. Treemaps in Power BI

21. Waterfall Charts in Power BI

22. Example in Power BI, SSRS
• Demo

23. Why R?
• most widely used data analysis software - used by 2M + data scientist,
statisticians and analysts
• Most powerful statistical programming language
• flexible, extensible and comprehensive for productivity
• Create beautiful and unique data visualisations - as seen in New York Times,
Twitter and Flowing Data
• Thriving open-source community - leading edge of analytics research
• Fills the talent gap - new graduates prefer R.

24. Growth in Demand
• Rexer Data Mining survey, 2007 - 2013
• R is the highest paid IT skill Dice.com, Jan 2014
• R most used-data science language after SQL -
O'Reilly, Jan 2014
• R is used by 70% of data miners. Rexer, Sept 2013

25. Growth in Demand
• R is #15 of all programming languages. REdMonk, Jan
2014
• R growing faster than any other data science language.
KDNuggs.
• R is in-memory and limited in the size of data that you
can process.

26. What do I need to install?
• Install R – www.r-project.org
• Install Rstudio – www.rstudio.com
• Handy Shortcuts
• Tab – autocomplete of available functions
• Control and Up Arrow – History
• Control and enter – executes the line of code

27. What tools do we have in R?
• 80% of your time will be spent preparing and wrangling data
• The remainder of your time will be spent complaining about it.
• dplyr: the essential data manipulation toolset
• In data wrangling, what are the main tasks?
• – Filtering rows
– Selecting columns of data
– Adding new variables
– Sorting
– Aggregating

28. Example in R
• Demo

29. The Big Data problem
• Reaction Time
• Enrichment
• Insights
• Optimize for query, not for storage.

30. Can you check the errors between 12.02 and 12.04
yesterday?

31. Can you check the errors between 12.02 and 12.04 last
Friday?
…. Are you kidding me?

34. What is Kibana?

36. Kibana
• It is highly customizable dashboarding
• It is constituted of panels:
– Time picker / Query / Filtering
– Charts / Table / Text

37. Flexible analytics and visualization platform
Real-time summary and charting of streaming
data
Intuitive interface for a variety of users
Instant sharing and embedding of dashboards

38. To better understand large volumes of data..
• easily create bar charts
• line and scatter plots
• Histograms
• pie charts
• maps.

39. To better understand large volumes of data..
• easily create bar charts
• line and scatter plots
• Histograms
• pie charts
• maps.

40. Kibana DataViz Types

41. Default Chart Types
Chart Type Basis Values Types Purpose
Histogram Timestamp based Count, Mean, Total Barlines, stacks,
percentages
Queries
Table Paging Fields list Highlighting,
sorting
Fine grained
analysis
Pie Charts Terms Missing terms,
other
Doughnut, legends,
tables
Proportion

44. Summary
• SSRS
• Excel
• Tableau
• Power BI
• Datazen
• Kibana