What are the 3 Main Goals of Data Visualization?

Here are the 3 Main Goals of Data Visualization. Improve your data viz with these three factors!

What are the 3 Main Goals of Data Visualization?

Transforming information into visualizations can help people comprehend challenging concepts. The three basic objectives of data visualization are Exploration, Monitoring, and Explanation. Most visualizations concentrate on a single objective, while others can cover more than one of them.


Exploratory data analysis (EDA) is the process of summarising data using statistical and visualization approaches in order to focus on key elements of the data for additional analysis. This includes analysing the dataset from a variety of perspectives and characterising and summarising it without assuming anything about its substance.

A data visualization that is centred on exploration and quick iteration might be helpful when users are seeking for an open-ended tool that enables them to identify patterns and insights in data. Tools used for exploration should be tightly integrated with those used for data collection (extract), cleaning (transform), and curation (load).

Before launching into statistical modelling or machine learning, it is important to perform exploratory data analysis to make sure the data is accurate and free of evident flaws. Every organisation's data science initiatives ought to include it.


A data visualization that is primarily concerned with monitoring is the best when users need to check on the performance of something. Dashboards and other monitoring tools should emphasise leading indicators and display data that is relevant to practical, immediate actions.

For many years, data monitoring has been transforming the commercial scene. Despite this, managing the enormous amounts of unstructured data coming from diverse sources hasn't always been simple for businesses. Additionally, the lack of technical proficiency among users has caused the generation of reports to be weeks late. Due to the quick-paced nature of the current setting, by the time a report is finished, the data has already lost its usefulness. In fact, according to experts, issues with keeping data current and usable cost US businesses more than $600 billion annually.

With the aid of a monitoring dashboard, you can follow your performance indicators and quickly visualise your data sets using cloud data analytics monitoring. You can either drill down and evaluate the details, or you can get a broad snapshot of your statistics.


A data visualization that focuses on explanation is helpful when consumers want to explore the "why" of a situation in greater detail than just the "what." Explanatory visualizations are typically hand-crafted to aid in the understanding of a complex subject by a large audience, and they cannot typically be mechanised.

The next level of analysis is explanatory. Instead of detailing what happened, you concentrate more on how, why, and what should occur next. In most circumstances, you communicate this information to the relevant decision-makers and stakeholders.

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