To deliver the best results, however, these solutions should provide powerful tools to build out the infrastructure for harnessing and aggregating data. The software also ought to streamline the process of discovering and sharing insights.
The following are some of the key features and capabilities that you should consider when buying a data visualization system:. Visual discovery. A useful feature that enables you to discover sequences, patterns, and outliers hidden in raw data. Visual analytics. The feature allows you to analyze large volumes of data using robust interactive visual interfaces. Visual pivoting. Data scientists and decision-makers often use pivot tables for big data.
Real-time collaboration. This capability allows team members to have a meaningful conversation about data discoveries. It enables decision-makers to collaborate in real-time and discuss insights, rather than sending screenshots and static files to one another.
Email reporting. Data visualization software also allows you to create schedules and have visual statistical reports delivered to your email inbox. Mobile support.
With mobile support, you can access relevant information and data visualizations anytime, anywhere. There is no doubt, data visualization software makes analysis and presentation of data a whole lot easier for analysts and decision-makers. Here are three data visualization software that offers powerful yet easy-to-use features:.
This data visualization software allows you to perform data discovery through an intuitive, drag-and-drop interface. No need for SQL. Everything from creating new exploration to building charts is simplified to expedite the entire process. In addition, Sisense allows you to customize dashboard layouts by dragging widgets on top of another. This data discovery application makes it super easy to collect, analyze, and visualize data.
It provides a variety of easy-to-use graphs and charts to choose from to create and customize interactive visualizations. Moreover, it can generate fully customizable and exportable reports. As such, users can easily share their analyses with their supervisors, colleagues, or stakeholders. This interactive JavaScript charting API is among the easiest data visualization software around for its easy configuration options that do not require extensive programming experience.
Thanks to its user-friendly interface, the solution allows you to create virtually any type of interactive chart, from error bars and column charts to bar charts and box plots, this can be used for all types of data visualization. Here are some of the best free data visualization software:. This enterprise-grade data visualization software may be known for its premium functionalities. However, this product also offers a free version—Tableau Public, a totally free, easy-to-use data visualization for non-commercial users.
The solution provides a huge swath of maps, charts, and graphs to help users visualize and publish data on topics that matter to them. In this way, it is easier to explore data without the hefty pricetag.
Microsoft Power BI Desktop. Coming from one of the most popular software providers worldwide, this platform offers top-notch business intelligence and data visualization options. The software offers a free plan that comes equipped with data exploration, preparation, and cleaning options.
Moreover, it allows users to create custom visualizations and publish them to the Power BI service. The only downside is that this free plan is only available for single users.
As such, it may not be ideal for mid-sized to large teams. Highcharts is an intuitive yet simple browser-based data charting API solution.
It offers a free version primarily for personal use, non-profit organizations, and school projects. With this, users get access to a wide selection of chart types, import and export data with ease, and even analyze data on-the-go with its mobile compatibility.
For those looking to perform more advanced data visualization processes, the platform can also be easily upgraded to paid versions. With his experience in software development and extensive knowledge of SaaS management, he writes mostly about emerging B2B technologies and their impact on the current business landscape.
However, he also provides in-depth reviews on a wide range of software solutions to help businesses find suitable options for them. Through his work, he aims to help companies develop a more tech-forward approach to their operations and overcome their SaaS-related challenges. Updated January 11, FinancesOnline is available for free for all business professionals interested in an efficient way to find top-notch SaaS solutions. We are able to keep our service free of charge thanks to cooperation with some of the vendors, who are willing to pay us for traffic and sales opportunities provided by our website.
Home Data Visualization Software. Why is FinancesOnline free. What is Data Visualization Software? How was this ranking made?
Select more products to compare. Zoho Analytics Our score: 8. Sisense Our score: 9. Looker Our score: 9. Periscope Data Our score: 9. Reveal Our score: 9. Tableau Our score: 9. Microsoft Power BI Our score: 9. Board Our score: 9. Domo Our score: 8. DbVisualizer Our score: 8. OpenRefine Our score: 8. Table of contents. Industry Report - Data Visualization Software for Leaders: those with a User Score of 8 or higher; this tier includes products that are currently leaders on the market and are appreciated by both experts and actual users.
Contenders: those with a User Score between 7 and 8; this tier includes high-quality products that still have some minor drawbacks that prevent them from becoming leaders on the market. They always represent well-designed tools that, over time, will most likely develop into market leaders as the missing features are added.
Rising Stars: those with a User Score between 6 and 7; this tier includes products that have high-potential but still lack some crucial features or services expected from a leading solution. They are products with solid foundations and a vision that makes us eager to see what they will become as their solution improves in the future.
Show less. Market Position A score between 1 and 10 based on popularity and market reach of each product. Rising Star. Front Runners. SAP Analytics Cloud 8. Our score and features analysis:. Customers company size. Sisense 8. Zoho Analytics 8. Looker 8. Domo 8. Microsoft Power BI 8. InsightSquared 7. Tableau 7. Oracle BI 7. QlikView 7. Staying nimble while connected is a win-win. Unleash the power of visual collaboration across the entire workflow, from idea to reality.
And as your business scales, Lucid provides the security and support you need to grow with confidence. Think big. Build faster. The intuitive virtual whiteboard where ideas ignite. Make it simple for your teams to brainstorm their best ideas and bring them to life. The intelligent diagramming platform that brings teams together so you can make better decisions and build the future. The cloud visualization solution that automatically generates accurate, dynamic cloud diagrams to help you understand and optimize your cloud environment.
Product suite Product suite See and build the future with a powerful visual collaboration suite. Product suite overview The intelligent diagramming solution to help teams turn complexity into clarity. Solutions Tap into the power of visual collaboration to launch ideas into action. Enterprise solutions See and understand your business Turn complexity into clarity. Span team silos Connect across silos and unleash the power of agile teams. Bring teams together Keep everyone connected, no matter where they are.
Visual learning Lucid for Education Empower students to succeed with the creative power of diagramming and design. Resources Helpful insights to get the most out of Lucid. Connect with us Customers. Job automations to set up customized tasks can be scheduled or based on a specific event.
Developed in under the name Hudson, Jenkins is an open-source CI automation server that can be integrated with several DevOps tools via plugins. By default, Jenkins assists developers to automate parts of their software development process like building, testing, and deploying. However, it is also highly used by data analysts as a solution to automate jobs such as running codes and scripts daily or when a specific event happened.
For example, run a specific command when new data is available. On the other side, the Jenkins Job DLS plugin provides users with the capabilities to easily generate jobs from other jobs and edit the XML configuration to supplement or fix any existing elements in the DLS.
Lastly, the Pipeline plugin is mostly used to generate complex automated processes. For this reason, they provide hundreds of plugins and extensions to integrate Jenkins with your existing tools. This way, the entire process of code generation and execution can be automated at every stage and in different platforms - leaving analysts enough time to perform other relevant tasks. All the plugins and extensions from Jenkins are developed in Java meaning the tool can also be installed in any other operator that runs on Java.
If you work for a company that produces massive datasets and needs a big data management solution, then unified data analytics engines might be the best resolution for your analytical processes. That said, Apache Spark is one of the data analysis tools on our list that supports big-scale data processing with the help of an extensive ecosystem.
A large ecosystem of data frames, streaming, machine learning, and graph computation. A collection of over operators for transforming and operating on large scale data. Apache Spark is originally developed by UC Berkeley in and since then, it has expanded across industries and companies such as Netflix, Yahoo, and eBay that have deployed Spark, processed petabytes of data and proved that Apache is the go-to solution for big data management.
Already in , Spark has officially set a record in large-scale sorting. Actually, the engine can be x faster than Hadoop and this is one of the features that is extremely crucial for massive volumes of data processing. You can easily run applications in Java, Python, Scala, R, and SQL while more than 80 high-level operators that Spark offers will make your data transformation easy and effective. As a unified engine, Spark comes with support for SQL queries, MLlib for machine learning and GraphX for streaming data that can be combined to create additional, complex analytical workflows.
Additionally, it runs on Hadoop, Kubernetes, Apache Mesos, standalone or in the cloud and can access diverse data sources. Spark is truly a powerful engine for analysts that need support in their big data environment.
Spreadsheets are one of the most traditional forms of data analysis. To look at spreadsheets in more detail, we have chosen Excel as one of the most popular in business. Pivot tables and building complex equations through designated rows and columns. Excel needs a category on its own since this powerful tool has been in the hands of analysts for a very long time. Often considered as a traditional form of analysis, Excel is still widely used across the globe.
Once this part is finished, you can export your data and send it to the desired recipients, hence, you can use Excel as a report tool as well. Creating pivot tables, managing smaller amounts of data and tinkering with the tabular form of analysis, Excel has developed as an electronic version of the accounting worksheet to one of the most spread tools for data analysts.
A wide range of functionalities accompany Excel, from arranging to manipulating, calculating and evaluating quantitative data to building complex equations and using pivot tables, conditional formatting, adding multiple rows and creating charts and graphs — Excel has definitely earned its place in traditional data management.
For that reason, we have decided to include of one these solutions on our list, although there are many others, industry-specific data analysis programs and software. Qualtrics is a software for data analysis that is focused on experience management and is used for market research by companies across the globe.
They offer 4 product pillars: the customer experience, brand, employee, and product experience, and additional research services performed by their own experts.
Their XM platform consists of a directory, automated actions, Qualtrics iQ tool, and platform security features that combine automated and integrated workflows into a single point of access.
Since automation is becoming increasingly important in our data-driven age, Qualtrics has also developed drag-and-drop integrations into the systems that companies already use such as CRM, ticketing, or messaging, while enabling users to deliver automatic notifications to the right people. This feature works across brand tracking and product feedback as well as customer and employee experience. Other critical features such as the directory where users can connect data from channels including web, SMS, voice, video, or social , and Qualtrics iQ to analyze unstructured data will enable users to utilize their predictive analytics engine and build detailed customer journeys.
Data science can be used for most software solutions on our list, but it does deserve a special category since it has developed into one of the most sought-after skills of the decade. No matter if you need to utilize preparation, integration or data analyst reporting tools, data science platforms will probably be high on your list for simplifying analytical processes and utilizing advanced analytics models to generate in-depth data science insights.
To put this into perspective, we will present RapidMiner as one of the top data analyst software that combines deep but simplified analysis. A comprehensive data science and machine learning platform with more than algorithms. Possible to integrate with Python and R as well as support for database connections e. RapidMiner is a tool used by data scientists across the world to prepare data, utilize machine learning and model operations in more than 40 organizations that heavily rely on analytics in their operations.
By unifying the entire data science cycle, RapidMiner is built on 5 core platforms and 3 automated data science products that help in the design and deploy analytics processes.
Their data exploration features such as visualizations and descriptive statistics will enable you to get the information you need while predictive analytics will help you in cases such as churn prevention, risk modeling, text mining, and customer segmentation.
With more than algorithms and data functions, support for 3rd party machine learning libraries, integration with Python or R, and advanced analytics, RapidMiner has developed into a data science platform for deep analytical purposes. The amount of data being produced is only getting bigger, hence, the possibility of it involving errors.
To help analysts avoid these errors that can damage the entire analysis process is that data cleansing solutions were developed. These tools help analysts prepare their data by eliminating errors, inconsistencies, and duplications enabling them to extract accurate conclusions from the data.
Before cleansing platforms were a thing, analysts would manually clean the data, this is also a dangerous practice since the human eye is prompt to error. That said, powerful cleansing solutions have proved to boost efficiency and productivity while providing a competitive advantage as data becomes reliable. The cleansing software we picked for this section is a popular solution named OpenRefine. Transform data to the format you desire, for example, turn a list into a table by importing the file into OpenRefine.
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