data visualization software

Best 5 Data Visualization Software of 2020

Data visualization software is a Business Intelligence resource, a kind of computer application that processes and analyzes data to produce quality and relevant insights, to help companies of all sizes, governments, and research centers to understand their processes.

It uses a variety of metrics, formulas, and stats to relate, compare, and measure indicators. The main functions of this software are data discovery, data management and reporting to establish patterns and predictions.

If you are looking for the perfect data visualization software for your company, we recommend you consider our list below. Check it out!

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How to improve business requirements with a data visualization software?

This software can help improve companies’ processes by generating insights for decision-making, integrating information from different systems, and making reports, analyses, and projections more understandable. Check it below.


Ability to integrate information from different business systems

Companies often have software to control the processes in their routines — ERPs, CRMs, and TMSs, for instance. All information generated in these systems must be treated and used together for decision-making. Data visualization software will quickly integrate all information from different sources.


Understandable reporting and analysis

A helpful data visualization software gives users the knowledge needed to deal with complex trends, and not just send mined information without treatment.

It has to offer a good data visualization, letting users understand different actions or strategies by graphics, reports, and interactive content to allow them to predict different scenarios and to achieve success in their businesses.


Historical analysis and reporting

It is required to identify the strengths and weaknesses of every company, their growth, the passing of the years, and the reasons behind it.

A data visualization software can provide users with a deeper insight into their businesses over time because they can analyze big and complex historical data: by extracting, manipulating, and making all processes’ information understood.


Future projections and forecasting

By analyzing and reporting historical data, the software enables the company to project findings into the future and find out what are the next steps to scale and become successful.


What resources are available to reach better results?

A data visualization software can operate in different ways:

  • On-premises: in-house platform installation by using company’s equipment, which integrates their IT infrastructure. The advantages are greater security and more control. However, maintenance is more expensive and scalability is limited to the available volume of resources.
  • Cloud implementation: there are many types of cloud computing available to host data visualization solutions, which include public, private, or hybrid clouds. The benefits are scalability, high availability of resources, greater possibility to download new tools, and less concern with updates.

It also includes features such as:

  • data mining: look into large amounts of data to identify new models and patterns;
  • online analytical processing (OLAP): allows users to quickly evaluate multidimensional data from different perspectives;
  • predictive analytics: accounts current and historical data to make projections about future opportunities and risks;
  • semantic and text analytics: extracts and interprets large volumes of text to recognize patterns, sentiment, and relations;
  • data quality management: helps companies maintain clean, error-free, and standardized data — an essential characteristic for data analysis from multiple sources;
  • extract, transform and load (ETL): collects data from outside sources, converts it, and store it into the database;
  • reporting tools for visualizations: supports users to create sophisticated graphical representations of data, using easy user interfaces.
  • dashboards: highlights key performance indicators (KPIs) that help managers to focus on important metrics;
  • report writers: allows users to design and create custom reports;
  • scorecard: gives numerical importance to performance and helps to map growth towards predetermined objectives.


What is the best 5 data visualization software in 2020?

1. Visually

Visually is a Rock Content platform that creates data visualization and turns numbers into visual content.

Using charts, maps, interactive content, infographics, motion graphics, explaining videos, histograms, scatter plots, regression lines, timelines, treemaps, and word clouds, the Visually platform reaches more details from data to leverage businesses results and generate better opportunities for brands.

Famous enterprises such as Salesforce, LinkedIn, American Express, Spotify, Visa, Rosetta Stone, Cisco, Gerber Life Insurance Company have already done projects with Visually.

The Visually data visualization software’s advantage is the fast collaboration with qualified professionals and the resources of the platform that streamlines the design process by putting the user in close communication and delivering data visualization content in record time:

  • after describing the demand to a rep, the creative brief could be made with data and all the information about the project;
  • a talent team, composed by designers, writers, developers, creative directors, and animators, initiate a kick-off project inside the Visually Workspace;
  • the user can communicate directly with them to achieve better feedback and quick reviews.


2. Sisense

Sisense data visualization software is for large enterprises or medium businesses, supported by Windows, Linux, Android, iPhone/iPad, Mac and browsers.

It could be deployed on-premises or on the cloud and it is available in ten languages, including English, Chinese, and Portuguese. You can make an annual subscription or acquire a quote-based.

It earned the 2019 Best Business Intelligence Award, 2019 Supreme Software Award, 2019 Expert choice’s Award, and it is used by famous enterprises and government agencies, such as Sony, Comcast, ESPN, and NASA.

It uses interactive resources into their drag and drop interface dashboards to unify all information, regardless of the complexity of data and turns it into insights that can be shared.

With In-Chip engines technology, Sisense handles complex and big data: the software uses CPU cache memory as well as processes data only when a new query is made, making it scalable and more convenient for users.

It also eliminates the need for many tools because it has complete resources to search, filter, and drill down into this data, taking the burden off IT departments and making IT professionals free to focus on their core routines. Sisense’s features are:

  • ad-hoc analysis;
  • in-house setup;
  • centralized data hub;
  • non-programming/SQL writing business query;
  • data collection, filtering, consolidation, and storage;
  • data connectors;
  • data export to various formats;
  • scalable data handling;
  • scalable analytics;
  • drag-and-drop functionality;
  • no restrictions on data size;
  • embeddable widgets and dashboards;
  • widgets library;
  • apps and sites integration;
  • data visualization tools;
  • metrics identification.


3. Periscope Data

Periscope Data was merged with Sisense. It is an advanced software supported by any programming language (SQL, Python, and R, for instance) that allows users to analyze, visualize, store, and report on data from various sources, connected with the platform. Periscope Data’s features are:

  • data engine;
  • cloud data storage;
  • data discovery and mining;
  • data cleansing;
  • predictive analytics;
  • natural language processing;
  • prototyping;
  • drag-and-drop interface;
  • data preparation;
  • managed redshift warehouse;
  • data lake integrations (Presto, Qubole, Athena);
  • materialized views;
  • R editor;
  • SQL editor;
  • Python editor;
  • data exploration;
  • custom visualization;
  • cohort grids;
  • charting;
  • radar charts;
  • mapping capabilities;
  • color themes;
  • gauge chart;
  • text overlays;
  • box plots;
  • full TV mode;
  • URL link sharing;
  • import and export to PDF;
  • shared dashboard passwords;
  • CSV disable options;
  • scheduled email alerts;
  • Slack integration;
  • annotation options;
  • user permissions;
  • user management API;
  • Git integration;
  • dashboard refresh management;
  • SQL alerts;
  • auto archive;
  • version control;
  • query management;
  • usage data;
  • two-factor authentication;
  • single sign-on;
  • HIPAA compliance management;
  • BAA compliance management;
  • white labeling options;
  • embed API;
  • render API.

It was built to serve businesses of all sizes, such as Adobe, Crunchbase, Flexport, EY, and ZipRecruiter. Their users could visualize data via interactive graphics, displays, and filters. Periscope Data’s advantages are:

  • easy-to-navigate interface;
  • optimized data analysis;
  • more efficient query management;
  • better and more engaging reports;
  • easier collaboration;
  • secure database.


4. Microsoft Power BI

Microsoft Power BI is a suite of business analytics tools designed to help companies to gather information, examine data, identify trends, share insights, and drive better decisions.

It is distinguished because Microsoft is expanding its capacity with new connectors (a MailChimp database, for instance) and resources: with Power BI Embedded, it is easy to embed the solution into custom developers’ apps, publish their reports, and data visualizations directly at web. The benefits of using Microsoft Power BI include:

  • unlimited access to on-premise and in-cloud data;
  • interactive visualization to share with audiences;
  • simplified answers to complex questions;
  • easier collaboration;
  • full access to a robust collection of learning materials;
  • unlimited connectivity.

Microsoft Power BI features’ include:

  • customizable dashboards;
  • datasets;
  • reports;
  • navigation pane;
  • Q&A question box;
  • help and feedback buttons;
  • ad hoc reporting;
  • ad hoc analysis;
  • online analytical processing (OLAP);
  • trend indicators;
  • interactive reports authoring;
  • complete reporting & data visualization tools.


5. Tableau

Tableau is a data visualization software that helps companies to visualize and understand their information processes. By giving a disruptive new approach when it comes to business intelligence, the platform allows businesses to quickly connect, visualize, and share data. Users can create and publish data visualizations without programming skills.

There are some types of Tableau products:

  • Tableau Desktop;
  • Tableau Server;
  • Tableau Online;
  • Tableau Prep.

Tableau also offers many benefits:

  • connection to multiple data sources;
  • intuitive and easy interface;
  • advanced collaboration;
  • several methods for data investigation;
  • flexible deployment;
  • reliable support.

Tableau features’ include:

  • patented technology from Stanford University;
  • toggle view and drag-and-drop;
  • list of native data connectors;
  • highlight and filter data;
  • shared, embed, and mobile-ready dashboards;
  • data notifications;
  • Tableau Reader for data viewing;
  • dashboard commenting;
  • creates no-coding data queries;
  • translates queries to visualizations;
  • imports all ranges and sizes of data;
  • creates interactive dashboards;
  • strings insights into a guided story;
  • metadata management;
  • automatic updates;
  • security permissions at any level;
  • Tableau Public for data sharing;
  • server REST API.


What all data visualization software have in common?

The most usual features of data visualization software include:

  • experimentation based on previous decisions;
  • A/B or multivariate testing;
  • predictive modeling or analytics;
  • mixtures data to see new patterns and relations;
  • statistical or quantitative analysis to explain the causes of the results.

There are some relevant requirements for data visualization software: data management and reporting resources. But the platform also has to be able to:

  • obtain complex data from all kinds of sources;
  • create relevant meaning and context for the main objective;
  • distribute data in visually informative tables, charts, and layouts;
  • provide advanced and more meaningful reporting and presentation features;
  • provide easy-to-configure interfaces;
  • be responsive;
  • be supported on different hardware, mainly mobile devices;
  • scale with several and complex data sets;
  • be embedded with information technology systems;
  • provide all requirements and tools for data security — backups, for instance;
  • favor collaboration.

All data visualization software lets users join, analyze, and draw information they require to make better and more correct decisions, work with strategic plans, get towards predetermined objectives, and increase SEO strategies.

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