Data Visualization is one of the most important part of data analysis. It has always been important to present the data in an understandable and visually appealing format. Data visualization is one of the skills that Data Scientists have to master in order to communicate better with the end users. There are various data visualization tools that a data scientist or a data analyst uses to present the data in explicable graphs, charts and also 3D models. 10 of the data visualization tools that we have discussed here are Tableau, Wolfram Alpha, MS Excel, Many Eyes, CartoDB, ChartBlocks, Charted, D3.js, DyGraphs and Visual.ly.
According to SiliconAngle, there was 2.5 zetabytes of stored data world over in the year 2012 and it is set to hit the 8 zetabytes mark by the end of 2015. To put things in perspective, this data has largely been produced by websites and cross platform transactions. Add to it the fact that there would be a total of 20 billion “smart” devices connected to the internet by the end of 2020 and the numbers can be baffling! Given that Facebook alone produces about 15 TB data on a daily basis today, imagine a situation where our refrigerators, microwaves, cars, fitness devices and a host of other connected devices start producing and storing data every second!
Data Visualization is a broad and generic term which is regularly used to describe the depiction of the results of data analysis, in a graphical or a pictorial format. The results of data analysis are usually produced in a text, or number format by the various tools used by data scientists. These results are not easily comprehensible by the end user. Data Scientists use various data visualization tools to present the data in a visually appealing format.
Data explosion of present century is the primary reason Data Scientists are in demand – more so in transaction driven industries such as e-commerce, retail, banking and finance, etc. That is why making sense of data assumes importance. Writing codes is one way to manipulate the data at hand and turn it into actionable insight. However, everyone is not a programmer and thanks to the data visualization tools that we cover in this article, everyone need not be a programming expert to tell stories from data. As Economist Ronald Coase puts it, “if you torture the data long enough, it will confess.”
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Data visualization allows data scientists to converse with their end users. The outcome of data analysis – is not immediately comprehensible to the people who do not directly deal with data. Data visualization bridges that gap and makes people appreciate the possibility of data analysis.
We are listing down some of the best used data visualization tools with examples to explain how exactly data is depicted to the end user.
One of the best interactive data visualization tools, Tableau has gained popularity around the world owing to its simple, drag and drop based user interface. It is a hit with executives and managers who do not have a technical background as one doesn’t have to be a coding expert to use it. It allows easy transfer of data to or from popular file formats such as xls, csv, xml, etc. and the user can draw up charts and histograms of varying complexities as and when needed.
Basic version of Tableau data visualization tool is free which can perform regular tasks such as:
The below Tableau visualization is used to depict a County View Health Index, which has the healthiest to the least healthy counties color –coded.
Image Credit :public.tableau.com
When we talk about numbers, statistics and visualizations, Wolfram Alpha inevitably finds a mention. It is a freely available statistics specific search cum calculation engine which is more than capable of producing customizable, informative representations such as pie charts and histograms. If you are using publicly available data, the corresponding charts and graphs can easily be uploaded on your blog or website through simple widgets.
Below is a depiction of how Wolfram Alpha presents the data of how people meet friends in Facebook.
In a rush to search for specialized tools, we often tend to forget that sometimes the old warhorse can get the job done just fine, without having to download, install and learn anything new. Excel is one such tool which has stood the test of time and is a jack of all trades. As long as the requirement doesn’t go beyond drawing basic bar graphs and charts, excel can turn out to be as good a companion as any other tool mentioned in this article. A vast majority of windows users are familiar with excel data visualization and the folks at Microsoft have kept upgrading it - maintaining its popularity.
Though excel can accomplish many of the entry level data exploration functions (including heat maps and scatter plots) its limitations are exposed when you want to go beyond the default set of formatting options related to colors, line and styles.
Image Credit : businessintelligence.com
Excel has had several extensions which were inbuilt and modified over the year to suit the requirements of the companies. There are many data visualization tools which had been inbuilt in excel like treemaps, and Excel 2016 has some more features to expand data visualization. More tools like Geoflow are additions on Excel to help data scientists use it for visualization. In the image below, Geflow is used to depict the power stations across US from the 1900s to 2008.
Big technology companies are often criticized for not supporting open research. IBM has taken a great initiative by developing Many Eyes and making the results public. It is a useful tool to quickly build informative infographics. It can process both publicly available datasets and user uploaded ones. It has been one of the pioneers of data visualization and even though there are strong rumors of IBM deciding to close Many Eyes, its utility, speed and simplicity is handy. Being hosted on the cloud, Many Eyes provides yet another advantage to the user as he need not install the software locally.
In the image below, the various food types are depicted with the help of a bubble chart in Many Eyes.
Image Credit: infosthetics.com
Till now we have discussed about tools that primarily process quantitative data. What if you need to integrate such data with maps? CartoDB is one such tool which allows easy integration of tabular data with maps. A .csv file containing a string of addresses can be uploaded and CartoDB will work its magic by converting them to latitudes and longitudes and plotting them on a map. The only downside is that it is free only up to 5 times usage, post which you must pay to use it.
CartoDB is mostly used in integrating the results of data analysis with maps which are then used for GPS, heatmaps, etc.
Image Credit: stamen.com
In line with the shifting customer preferences towards cloud based solutions such as SaaS, PaaS and IaaS (Software as a Service, Platform as a Service and Infrastructure as a Service), ChartBlocks has built a completely online solution where you get your desired data stories without actually owning the software – at a fraction of the cost.
ChartBlocks is a well-designed, online chart builder which allows easy building of basic chart types. It facilitates integration with multiple external data sources (including spreadsheets and databases) from where you can source in data, build all the basic chart types and export or embed the resultant file anywhere you want to.
Image Credit: sitemap.com
If you need to present an elementary data visualization graphic, Chartered is definitely worth a consideration. It has been developed by the product science team at Medium and can be linked to an online google spreadsheet or a .csv file for feeding input. Being open source, it would surely attract developers, who can use a customized version to host on their own websites and blogs. The basic version has been coded to sync data with the source every 30 minutes, which ensures the chart is up to date.
The tools mentioned above need little or no programming language. For users familiar with programming languages and developers who would like to embed charts and graphs in their web page, there are a number of tools at their disposal. Some of the more popular tools are:
Data Driven Documents gives developers the power to integrate HTML, CSS and SVG into their code to produce highly customized data visualization. Not shipping with standard templates is one of its plus points, as the developers are free to represent data in any manner they want. Being open source, it is always free and there is always an online community to exchange information with.
Before you decide on using it, do keep in mind that is has a steep learning curve and there are compatibility issues with older browsers as it is known to work well only with IE9 and above.
Image Credit: anna.ps
If you have a development team working on a java based platform that needs to include charts derived from huge data sets, Dygraphs is an excellent option. It irons out browser compatibility issues that impede D3, as it works with all common browsers. Keeping in mind the ever growing usage of smartphones and tablets, it allows you to include touch friendly features such as pinch to zoom. Dygraphs charts can be made interactive as they support features like drag to zoom, shift-drag, mouse over, etc.
Image Credit: opsly.com
Visually specializes in creating beautiful visualizations and infographics. Just 4 years old, it has succeeded in building up a community of publishers, designers, developers and researchers. Presently they are developing a tool which would allow users to build their own infographic through an automated service. It is capable of pulling data from all the common storages such as excel, csv, databases and many more. Visually, the parent company, has already got a number of fortune 500 clients in its client list.
The below infographic is based on the analysis of the survey data on baby boomers.
Image Credit: blog.visual.ly
CLICK HERE to view the complete PPT on Data Visualization Tools
There are many great data visualization tools in the market and it is quite possible that we have missed out on some really good tools in our list. Please feel free to list down in the comments any data visualization tool that you feel should be mentioned in our list.
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