Community Blog A Guide to Data Visualization Definition, Tools and Examples

A Guide to Data Visualization Definition, Tools and Examples

Data visualization uses statistical graphs, charts, infographics and other tools to visually convey quantitative information to help users analyze and reason about data.

Data visualization refers to the presentation of data in a graphical manner. It enables decision-makers grasp complex concepts or identify new data patterns by having a visual view of data analytics. With interactive visualization, you can enhance the idea of data visualization by using technology to convert data into charts and graphs.

Understanding Alibaba Cloud DataV - A Powerful and Accessible Data Visualization Tool

Alibaba Cloud DataV is an effective data visualization tool that allows business decision-makers to conveniently understand data patterns, relationships, and trends.

Data Visualization for Businesses

Is data visualization a new concept? Why is it important?

Data visualization is not new. Businesses have been generating reports using maps, graphs, and charts as a way to summarize data. Data visualization is important mainly because of the way the human brain is designed to process information. It is always much easier to grasp information by supplementing text-based reports with graphs and charts.

For businesses in particular, data visualization cuts out the cumbersome process of data comprehension and offers users the ability to process and make sense of data using visually-presented and interactive dashboards. Data visualization tools allow users the opportunity to analyze trends interactively, helping businesses to conveniently identify relationships and draw inferences from data.

Challenges of Data Visualization

Despite the significant advantage of data visualization for businesses, it comes with its own set of challenges.

  1. Data Collection: Users of data visualization tools often find themselves with data from different data sources. This requires programmers to decode and maintain the various access interfaces. As the number of data source increases, users might often come across the need to find assistance in extracting useful data and upgrading it regularly.
  2. Varied Level of Understanding: Instances may arise where people habituated to seeing basic excel graphics fail to comprehend anything fractionally more complex. Additionally, there might be users who would be of the notion that interaction within data visualization is insignificant and is more of a luxury and not a necessity.
  3. Combining Similar Data from Multiple Sources: For businesses, nothing is more precious than valuable data. Organizations gather data, process it, and then try to make sense out of it. However, the challenge that arises is that relevant data often exists in more than one location. Often, people confuse data visualization tools whenever they encounter such a crossroad.
  4. Time Consuming Process: Gathering data, processing it, and designing relevant graphics from scratch is a cumbersome task. Furthermore, designers have to consider screen resolution, graphical responsiveness, data readability, aesthetic, and content-design relationship. These factors add to the time required to create a relevant graphical representation of data.
  5. Lack of Data Analysis Supporting Tools: Third-party tools available in the market often lack the ability to support Big Data analysis and presentation. Moreover, there are insufficient tools that are capable of visualizing and analyzing data stored in relational databases and spatiotemporal data.

Taking into consideration the importance of data visualization and the challenges that businesses face while attempting to use data visualization, Alibaba Cloud introduced its data visualization tool – DataV.

Related Blogs

Database Visualization using Metabase - Install Metabase on CentOS 7

In this tutorial, we will install Metabase on an Alibaba Cloud ECS CentOS 7 server to achieve data visualization.

Metabase is an open source application for visualizing your database and get insights from it. Metabase provides an intuitive and easy to use web-based interface for running queries on a database without writing a SQL statement. It works with almost all popular databases such as MySQL/MariaDB, Postgres, Mongo, SQL Server, Druid, H2, SQLite, and Oracle, etc. Data can be obtained in raw tables or beautiful graphs or charts. Metabase refers the queries to a database as questions. It lets you save the questions once asked, saved queries can be repeatedly executed to get the answers quickly. It also lets you create dashboards in which you can add multiple questions to get all the important insights in one place. Dashboards are auto-refreshed every time and can also be shared among your team members.

This tutorial is a port of How to install Metabase on Ubuntu 16.04. In this tutorial, we will install Metabase on CentOS 7 server. We will use PostgreSQL to host the Metabase database. We will also set up Nginx as a reverse proxy and secure the Metabase instance using Let's Encrypt SSL.


  1. Alibaba Cloud ECS instance with CentOS 7.4 64-bit installed.
  2. Firewall or Security group rules configured to allow the port "80", "443".
  3. A domain name that needs to be pointed towards your ECS instance.

You can follow the "Quick Start Guide" to create the instance and steps to connect to your instance. This tutorial assumes that you have created your Alibaba instance and "" is the public IP address assigned to your CentOS instance. You have also configured "metabase.example.com" to point to your CentOS instance. Once you have connected to your instance via SSH, run the following command to update the repository cache and the base system.

Deciphering Data to Uncover Hidden Insights – Data Stories (1)

This article describes the various features of QuickBI. We will be analyzing and visualizing a use case to help you create compelling data stories with QuickBI.

In the previous "Deciphering Data to Uncover Hidden Insights" series, we covered three topics of data analytics, including:

  1. Understanding the Data
  2. Data Wrangling and Ingestion
  3. Data Modeling

For me, "the best vision is insight." As per the saying, I like to walk you through in the process of deciphering data to uncover hidden and valuable insights for your business. In this article, I want to share how to visualize the data to tell compelling data stories according to your business scenario in Alibaba Cloud's Quick BI data visualization tool.

Visualizing Data (Conceptual)

"A picture is worth a thousand words "- When you're attempting to comprehend the information from the data and to discover relationships between your data, which might include thousands or millions of variables in front.

Visualization becomes inevitable in the world of Big Data; Data visualization tools and technologies are essential to analyze massive amounts of information and it allows us to make data-driven decisions.

What Is Data Visualization?

Data visualization refers to the pictorial representation of data. Information could be visualized in many ways including infographics, charts, graphs, and maps, each of which can offer a specific insight. Visual elements pave the way to see and understand patterns, outliers, and trends.

At its core, data visualization has three purposes:

  1. Reduces the complexity and ambiguity in the data and gives us business value.
  2. Promotes the understanding of data by representing in a visually appealing manner.
  3. Improves the decision making by allowing us to make data-driven decisions easily.

Why Data Visualization?

"Data Visualization plays an inevitable role in the modern business world." Data visualization ought to be insightful, efficient, appealing, and in several cases interactive too.


The basic purpose of the visualization or the canvas is to inform a meaningful information to the consumer. Envision the basic forms of visualizations like Tile or Bar or Pie, everybody is acquainted with these visuals and can quickly infer the intended point they represent. Since we're currently aggregating information and displaying it pictorial format it should convey the message that the aggregated information is telling us which becomes harder with a large amount of data.

Telemetry Data Collection, Query, and Visualization with Istio on Alibaba Cloud Container Service for Kubernetes

This article uses an official example to explain how to use the Istio functions of collecting, querying, and visualizing telemetry data.

In our previous articles, we have demonstrated how to deploy an application in the Istio environment with an official example, as well as explored how to configure intelligent routing and distributed tracing with Istio.

This article continues to use this example to explain how to use the Istio functions of collecting, querying, and visualizing the telemetry data.

Prometheus is an open source system released by CNCF. It provides the real-time monitoring, alerting, and time series database (TSDB) functions for the cloud native applications.

Collect Telemetry Data

First, refer to the metrics and log configurations defined in the official documentation to create a new_telemetry.yaml file.

Run the istioctl command to create the new configuration, as shown below:

istioctl create -f samples/bookinfo/new_telemetry.yaml
Created config metric/istio-system/doublerequestcount at revision 2611607
Created config prometheus/istio-system/doublehandler at revision 2611608
Created config rule/istio-system/doubleprom at revision 2611609
Created config logentry/istio-system/newlog at revision 2611610
Created config stdio/istio-system/newhandler at revision 2611611
Created config rule/istio-system/newlogstdio at revision 2611612

In the Kubernetes environment, run the following command to check that Prometheus is running properly:

kubectl -n istio-system get svc prometheus
prometheus   ClusterIP   <none>        9090/TCP   16h

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Quickly Generate Business Intelligence Diagrams with QuickBI

Quickly learn how to use QuickBI to generate visual charts. This course offers a complete explanation of how to import data sources, create datasets, and produce dashboards.

Quickly Generate Large Dashboards for Data Visualization

Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects contained in graphics. By using data visualization, data can be displayed through a dashboard intuitively and understandably. This course can help the data scientists learn how to create a large panel using Alibaba Cloud's DataV.

Data Visualization Using Python

Data visualization capabilities are very important. A beautiful and clear charts can help you understand the data intuitively when you explore and analyze data, Data visualization also plays an important role in your interactions with customers, and it helps you communicate the quantitative characteristics of the data.

Related Market Products

Data Visualization Using Python

Through this course, you will learn what is python visualization and how to use python visualization tools to generate plots to visualize data.

Quickly Generate Large Dashboards for Data Visualization

Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects contained in graphics. By using data visualization, data can be displayed through a dashboard intuitively and understandably. This course can help the data scientists learn how to create a large panel using Alibaba Cloud's DataV.

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Data visualization - Web Application Firewall

Based on the detailed website logs collected by WAF, WAF provides the data visualization service. By converting the data into a visual big screen, you can monitor and understand the real-time attack and defense situations of your website. This provides you with visual and transparent data analysis and decision-making capabilities to keep your website security.


Currently, the WAF data visualization service provides the following two visual screens for your choice:

WAF Real-time Attack and Defense Situation Screen

WAF real-time attack and defense situation screen is updated every second. It displays current day's website visit and overall interception situations for all your websites that protected by WAF. This screen focus on displaying the stability of the website service and the quality of the network service.

Table structure visualization - Data Management Service (DMS)

This section introduces table structure visualization in Data Management Service (DMS).


When creating or arranging new and existing tables, you may need to learn the structure of all tables. The traditional method uses commands to view and copy structures, table by table, or uses data visualization tools to display the structures and capture screenshots.


You can use the generate documents feature of DMS to quickly generate the structures of all tables in the database. You can then view the structures online or export the structures to Word, Excel, or PDF files.

Related Products


DataV is a powerful yet accessible data visualization tool, featuring geographic information systems allowing for rapid interpretation of data to understand relationships, patterns, and trends. All packed into a user-friendly interface.

Quick BI

Delivering analytic capabilities once reserved for professional analysts, Quick BI allows you to perform data analytics, exploration, and reporting on mass data with drag-and-drop features and a rich variety of visuals. Quick BI enables users to perform data analytics, exploration, and reporting, and empowers enterprise users to view and explore data and make informed, data-driven decisions.

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