Tools and Technology

Skill level:

• Do you already have people skilled with a particular software? Learning any new tool will require time and effort.
• Does the software require coding or programming skills? Do you have those skills? Or access to training?

Your data:

• How much data do you have?
• Where is your data stored? Cloud or local storage? Web-based or desktop? Can it be public, or does access need to be restricted?

End product:

• What kind of user interface do you want? Real-time data? Synchronizations? Stand-alone or integrated within a business intelligence platform?

Features:

• Does the software have the type of visualization that makes the most sense for your data and the point you are trying to convey?
• What features do you really need? 2D or 3D? Variable axis scales? Geospatial configurations? …Sometimes simpler is better.
• Can you easily update your dataset without having to redo the visualization? Can you easily convert from one visualization to another to explore which visualization works best?

Budget:

• Do you have any money set aside to pay for visualization software?  Or does your IT department have any existing contracts with companies with visualization software?
• Be careful – there are several ‘free’ versions available, but when deploying a visualization or report, exposes your data to the public.

Baker, P. (2019, March 5). The best data visualization tools of 2018. PC Magazine. Retrieved from PC website.

Dingeldein, T. (2019, October 28). Top 5 free data visualization tools to grow your business [Blog post]. Retrieved from Capterra website.

Marr, B. (2017, July 20). Seven best data visualization tools in 2017. Forbes. Retrieved from Forbes website.

Suda, B., & Hampton-Smith, S. (2019, February 12). 38 best tools for data visualization. Creative Bloq. Retrieved from Creative Bloq website.

Excel

• Spreadsheet software that provides calculations, graphing tools, pivot tables & charts, and a macro programming option.
• Best used for conditional formatting and building great charts to add meaning to basic tables, pivot charts, PowerPoint-friendly.
• Limitations include size of dataset, conversion problems with scientific data.

Skill Level:

No coding

Max Size:

2 GB

Data Stored:

Locally

Interactive:

Limited

Free Version?:

Discounts often available for university faculty, students and staff.

Tableau

• Ability to connect to multiple data sources, combine disparate data without writing code and create interactive visualizations and dashboards on the fly.
• Best used for fast actionable insights, statistical analysis, interactive maps, and sharing dashboards.
• Can be cost prohibitive, requires SQL knowledge if wanting to connect to a database and has no concept of versioning.

Skill Level:

Mostly no coding, but minimal SQL may be required.

Max Size:

Does not have any enforced row or column limits for the amount of data that can be imported.

Data Stored:

Locally or Cloud

Interactive:

Yes

Free Version?:

Yes, but when publishing reports or dashboards, data is made public.

Google Data Studio

• A dashboard and reporting tool that is very user-friendly with drag and drop features, and is easy to connect to other Google data sources (ie. Google Analytics and Google Sheets).
• Best used for interactions with visualizations including filtering through content with dimension and date range selectors, and sharing and setting permissions for viewing reports and dashboards.
• Limitations include being available only in beta, will only connect to a limited number of data sources, limited types of visualizations, and doesn’t allow you to bring together more than one data source at a time.

Skill Level:

No coding

Max Size:

Most charts now allow up to 20 dimensions and 20 metrics. Time series support up to 20 metrics. Tables support 10 dimensions and up to 20 metrics.

Data Stored:

Cloud

Interactive:

Yes

Free Version?:

Yes, with a Google account or Google Cloud Platform customers.

Microsoft Power BI

• A suite of business analytics tools for analyzing data and sharing insights.  Allows for simple uploading of data from many sources, including .xls, .csv, and .json. Can create custom reports and dashboards, with over 20 built-in visuals and an active community for custom visualizations.
• Best used for combining data from multiple data sources, custom and interactive visualizations, and the ability to access data and reports from anywhere.
• The free version only allows public sharing, and reports and dashboards can only source data from a single dataset.

Skill Level:

No coding

Max Size:

Please refer to: link

Data Stored:

Locally or cloud

Interactive:

Yes

Free Version?:

Yes, but when publishing reports or dashboards, data is made public.

D3.js

• A Javascript library for producing interactive data visualizations in web browsers.  It uses scalable vector graphics (SVG), HTML5 and CSS standards.
• With minimal overhead, D3 is extremely fast, capable of handling large data sets and dynamic behaviour for interaction and animation.
• D3.js can be rather cumbersome for small amounts of data.  In addition, it cannot easily conceal original data nor generate pre-determined visualizations for you.

Skill Level:

Javascript required, SVG, HTML and CSS optional

Max Size:

Rendering is based on number of SVG objects used.  Please refer to link for some more details.  Pre-rendering on the server side is recommended.

Data Stored:

Locally or cloud

Interactive:

Yes

Free Version?:

Yes

Python

• Python is a high-level programming language that is free to use and is designed to be easy to read and implement.  A few Python libraries that are designed in particular for data visualizations include matplotlab and ggplot.
• Python is widely used in the whole data science workflow (including related technologies like machine learning, natural language processing, etc.) and is becoming a very popular language.

Skill Level:

Python coding skills are required.

Max Size:

N/A

Data Stored:

Locally or cloud

Interactive:

Yes

Free Version?:

Yes

Plot.ly

• A charting library for creating interactive graphs and charts containing some 20 chart types, including 3D charts, statistical graphs, and SVG maps, built on top of open source software.
• Best used for when you need to build highly interactive graphs, has a large number of available visualizations, and  includes geo data and maps.
• More of a demand on internal system resources than other products.  Some previous knowledge of Python or Matlab would be an asset.

Skill Level:

Python and Matlab experience would be an asset.

Max Size:

Too much visualized data can cause browsers to freeze or fail to load.

Data Stored:

Locally or cloud

Interactive:

Yes

Free Version?:

Yes but there is a maximum limit of 100 image exports and chart saves per day.

Google Charts

• Google Charts is another way to present interactive data visualizations on your websites using simple Javascript and pre-defined charts/objects provided by Google.
• The graphs are customizable and rendered using HTML5/SVG allowing cross browser compatibility.  It is considered easy to learn and is completely free with a Google account.
• Some downsides include limited customization, minimal statistical processing, and Google having your data.

Skill Level:

No coding (except if you want to customize using Javascript)

Max Size:

Based on server and webpage loading on client side.

Data Stored:

Cloud

Interactive:

Yes

Free Version?:

Yes (with Google account)