In the contemporary business marketplace, data visualization refers to the representation of information in the form of a chart, diagram, or picture; which helps in catering to key business insights pretty well.
Data visualization animates the data beyond the management capacities of the stakeholders and helps them make sense of the generated data.
Data visualization will often serve an integral part in helping stakeholders to uncover key patterns, trends, and anomalies in the data.
The statistical representation from the Fortune Business Insights above showcases the Global Data Visualization Market size to grow at a CAGR of 10.2%, reaching the target of 19.2 billion by the year 2027, starting in 2019.
The driving factors for such stupendous growth could be listed as the widespread adoption of the Internet of Things (IoT) and Artificial Intelligence (AI) resulting in a surging data pool, thereby creating better market opportunities in the years to follow.
Data visualization fosters visually interactive ways to predict and infer data via patterns, comparisons, graphics, histograms, heatmaps, infographics, scatter plots, etc.
There is numerous data visualization software that help run data smoothly such as HighCharts, PowerBI, Leaflet, Tableau, Echarts, D3.js, Sisense, etc.
Still, Why is There a Need to Visualize Data?
A simple answer to that would be data presented in an attractive easy-to-comprehend visual that makes it easier for the viewers to interpret and understand the same. Easy data fosters convenient data analysis and helps draw actionable data-driven business insights.
Big data visualization makes a difference by analyzing industrial data by sending instant alerts. It also helps by analyzing social comments which assist the organizations to turn to sentiment analysis instantly to contain any difficult business situation.
Certified data scientists make the stakeholders aware of the changing market scenario of their business entity via consumer behavioral study, so data visualization helps them take control of any adverse consumer behavior in the future. They put in place some clever data science tools that help them draw key business insights.
13 Best Data Visualization Tools to Master in 2023
1. Tableau- Ranked among the top data science tools, Tableau comes packed with flexibility in usage and offers mapping capabilities, with access to files via the cloud and data warehouse.
2. Data Wrapper- Specifically designed for journalists, it includes an in-built color blindness checker and is compatible with all operating systems which require no prior technical knowledge.
3. Plotly- An analytical tool that is intuitive and enables smooth collab among teams and supports R, Python, and other programming languages.
4. Dundas BI- It offers high customization with interactive scorecards, maps, gauges, and charts and simplifies data.
5. Infogram- It offers excellent customer support with an easy embedding feature and offers quick data transfer into exciting content for users with project templates and minor modifications in place.
6. JupyteR- This web-based application offers rapid prototyping, with visually appealing results and facilitates easy sharing of data insights.
7. Google Charts- It works well with dynamic data and is convenient to customize, with a range of chart formats available.
8. Chart.js-
9. D3.js- Data-Driven-Documents (D3.js) uses HTML, CSS, and SVG to draw impressive charts and diagrams and is a great tool for non-programmers as well.
10. Visual.ly- Visual.ly is an amazing output quality data visualization tool that is easy to produce with superb graphics and link opportunities.
11. Sisense- Sisense is popular for providing high customer support with quick upgrades and a reliable interface and is ideal for critically targeted projects.
12. QlikView- QlikView comes with a user-friendly interface, with zero maintenance, and offers cost-effective business solutions.
13. Microsoft Power BI- With Power BI, data access from different data sources is made possible and brings along interactive dashboards so that users can filter and highlight features with a click of a button.
Data Visualization technology has been there for decades, which could be traced down to manual methods of computation. Data visualization has become more social nowadays, as there is a high degree of interaction from the followers’ end as well.
Today, numerous data science certification programs are designed in such a way to keep in mind the necessity of data visualization techniques, so much so that it imparts key data visualization skills to dynamic data science professionals.
Make the most of these intelligent data science tools in 2023 to prove yourself to be an asset for your future organizational success!
