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data visualization tools

Big Data Visualization Tools for Businesses

Let’s say you are a proud owner of a gold mine but you can’t harness the gold from that mine. So, what’s the point in being the owner? Is there any? The condition is the same with big data. There is no point in collecting large chunks of big data if you fail to churn it and harness the information lying beneath it. To resolve this issue, data visualization tools are the exact weapons you need. These tools show us various insights into the collected data. Big names like Google and Microsoft collect and manipulate big data to design the future of their business strategies. Today, we will discuss some of these popular visualization tools for big data.

data visualization tools

1. Google Chart

Google is an obvious benchmark and well known for the user-friendliness offered by its products and Google chart is not an exception. It is one of the easiest tools for visualizing huge data sets. Google chart holds a wide range of chart galleries, from a simple line graph to a complex hierarchical tree-like structure and you can use any of them that fits your requirement. Moreover, the most important part while designing a chart is customization and with Google charts, it’s fairly Spartan. You can always ask for some technical help if you want to dig deep. It renders the chart in HTML5/SVG format and it is cross-browser compatible. Added to this, it also has adopted VML for supporting old IE browsers and that’s also cross-platform compatible, and portable to iOS, and the new release of Android. The chart data can be easily exported to PNG format. Consequently, Google chart is quite efficient in handling real-time data. You can also endorse data from other Google products like Google Maps with your existing data to make an interactive chart and control them from an interactive dashboard. Furthermore, the service is absolutely free with strong Google support.

2. Tableau

Tableau desktop is an amazing data visualization tool (SaaS) for manipulating big data and it’s available to everyone. It has two other variants “Tableau Server” and cloud-based “Tableau Online” which are dedicatedly designed for big data-related organizations. You don’t have to be a coder to use this tool. This tool is very handy and provides lightning-fast speed. The canvas or dashboard is user-friendly and ‘drag and drop’ compatible, therefore, it creates a homely atmosphere in any working environment. You can connect all your data from as little as a spreadsheet to as big as Hadoop, painlessly, and analyze deeply. Tableau Desktop is free for students and instructors, otherwise, Tableau desktop charges $999 and $1999 for personal and professional editions respectively for 1 year with support. Read our detailed review of Tableau here.

3. D3

D3 or Data-Driven Document is a Javascript library for big data visualizations in virtually any way you want. This is not a tool, like the others and the user needs a good grasp of javascript to give the collected data a shape. The manipulated data are rendered through HTML, SVG, and CSS, so there is no place for old browsers (IE 7 or 8) as they don’t support SVG (Scalable Vector Graphics). It is not a monolithic framework that it has to seek for every opportunity, instead, it solves the problem from the crux. It allows you to bind arbitrary data with DOM (Document Object Model) and apply the data-driven transformation to the data with a smooth transition and animation effect (optional). D3 is extremely fast and supports large data sets in real-time. It also produces dynamic interaction and animation in both 2D and 3D with minimal overhead. The functional style of D3 allows you to reuse codes through the various collection of components and plug-ins.

4. Fusion Chart

Fusion chart XT is a Javascript charting library for the web and mobile devices, spread across 120 countries with clients such as Google, Intel, Microsoft, and many others. However, you need a bit of knowledge of Javascript for implementing it. Technically, it collects data in XML or JSON format and renders it through charts using Javascript (HTML5), SVG, and VML format. It provides more than 90 chart styles in both 2D and 3D visual formats with an array of features like scrolling, panning, and animation effects. It also provides 950+ maps of various places around the globe. Exporting charts is painless here, you can export any chart in PNG, JPG, or PDF format anywhere. Fusion Charts is available on Android, iPhone, iPad, MAC, and Windows. However, this tool doesn’t come for free. Its pricing range starts from $199 (for individual developers or freelancers) for one year and updates with one-month priority support.

5. Highcharts

Highcharts is a charting library written purely in Javascript hence, a bit of knowledge of Javascript is necessary for implementing this tool. It uses HTML5, SVG, and VML for displaying charts across various browsers (from IE6+) and devices like android, iPhone, etc. For any execution, it requires two .js files: the Highcharts.js core and jQuery or Mootools or prototype platform, which are mostly available on regular web pages. This tool also comes with a range of charts viz. line, bar, column, pie, etc. This tool is efficient enough to process real-time JSON data and represents them as a chart mentioned by the user. If you are an enthusiastic programmer you can download its source code and modify it as per your need. This tool is available for free to developers and the deployment price starts at $399. It has a huge client base which includes Facebook, Spandex, Visa, Nokia, and many more.

6. Canvas

Canvas.js is a javascript charting library with a simple API design and comes with a bunch of eye-catching themes. It is a lot faster than the conventional SVG or Flash charts. It also comes with a responsive design so that it can run on various devices like Android, iPhone, Tablets, Windows, Mac, etc. The chart gallery consists of 24 different types of charts but the USP is its speed. It can render 100000 data points in just 100 milliseconds. Therefore, if you are looking for a high-performance javascript chart, Canvas can be your best bet. It boasts of some business giants like Intel, Apple, Boeing, and EMC2 in its clientele. However, this tool is free for non-commercial usage.

Update: We have added more big data tools to the list on 03/07/2017

7. Qlikview

Qlik is one of the major players in the data analytics space with their Qlikview tool which is also one of the biggest competitors of Tableau. Qlikview boasts over 40,000 customers spanning over 100 countries. Qlik is particularly known for its highly customizable setup and a host of features that help create the visualizations much faster. However, the available options could mean there would be a learning curve to get accustomed to the tool so as to use it to its full potential. Apart from its data visualization prowess, Qlikview also offers analytics, business intelligence, and enterprise reporting features. The clean and clutter-free user experience is one of the notable aspects of Qlikview. Qliksense is a sister package of Qlikview which is often used alongside the former to aid in data exploration and discovery. Another advantage of using Qlikview is the strong community of users and resources which will help you get started with the tool.

8. Datawrapper

Datawrapper is a data visualization tool that’s gaining popularity fast, especially among media companies that use it for presenting statistics and creating charts. It has an easy-to-navigate user interface where you can easily upload a CSV file to create maps, charts, and visualizations that can be quickly added to reports. Although the tool is primarily aimed at journalists, its flexibility should accommodate a host of applications apart from media usage.

9. Microsoft Power BI

Microsoft Power BI is a suite of business analytics tools from Microsoft primarily meant for analyzing data and sharing insights. It enables you to explore and dig insights out of your data via any device you use – desktops, tablets, or smartphones. It helps you derive quick answers from the data and also can connect to on-premises data sources for real-time mapping and analysis. Your data source or format won’t be a limitation with Power BI as it lets you connect hundreds of sources such as streaming data, data on cloud services, excel spreadsheets, and most other data file formats. Power BI is considered one of the best data visualization tools by industry experts and is being used across industries like finance, and sales to operations. For basic requirements, the tool can even be used for free as it lets you analyze up to 1GB of data per user account without a paid subscription.

10. Oracle Visual Analyzer

Introduced in 2015, this web-based tool within the Oracle Business Intelligence Cloud Service claimed a spot in the Magic Quadrant Business Intelligence and Analytics Platform report by Gartner. Interactive visuals and highly advanced analysis clubbed with a customizable dashboard are some of the key features of Oracle Visual Analyzer. Being highly scalable, this data visualization tool is very suitable for enterprises with large-scale deployments where deep insights and well-curated reports are essential. Every bit of data carries a story with it and these data visualization tools are the gateway to fathom the story it tries to tell us. It helps us to understand the current statistics and the future trends of the market.

Frequently Asked Questions

How do these big data visualization tools integrate with existing data management systems or databases?

Most big data visualization tools are designed to integrate seamlessly with existing data management systems or databases. They achieve this through APIs, direct connectors, or plugins, providing native support for a wide range of data sources, including SQL databases, cloud storage solutions, and NoSQL databases. This ensures users can easily import and synchronize their data for visualization.

What are the specific security features or protocols these tools offer to protect sensitive data during the visualization process?

Regarding security, these tools implement several measures to protect sensitive data. This includes encrypting data both in transit and at rest, ensuring that information remains secure during transfer and storage. They also offer role-based access control (RBAC) and authentication mechanisms to restrict access to sensitive data based on user roles. Furthermore, they comply with international data protection regulations, such as GDPR and HIPAA, to ensure user data privacy is maintained.

Can these big data visualization tools handle real-time data streaming, and if so, how do they manage the performance and latency issues associated with real-time data processing?

For real-time data streaming, tools like Power BI and Oracle Visual Analyzer are capable of handling and visualizing data as it is generated. They address performance and latency issues through optimized data processing engines and offer the ability to adjust the granularity of data updates. This balance between providing real-time insights and maintaining system performance allows organizations to make timely decisions based on the latest data.

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