BASIC DATA VISUALIZATION HOW TO
BASIC DATA VISUALIZATION FULL
BASIC DATA VISUALIZATION SERIES

Together with the demand for data visualization and analysis, the tools and solutions in this area develop fast and extensively.

Matrix is one of the advanced data visualization techniques that help determine the correlation between multiple constantly updating (steaming) data sets. They can be hierarchical, multidimensional, tree-like. Among the most popular map visualizations are heat maps, dot distribution maps, cartograms.ĭiagrams are usually used to demonstrate complex data relationships and links and include various types of data in one visual representation. They allow locating elements on relevant objects and areas - geographical maps, building plans, website layouts, etc.

Maps are popular techniques used for data visualization in different industries. When it comes to big data, analysts often use more complex box plots to visualize the relationships between large volumes of data. Scatter and bubble plots are some of the most widely-used visualizations. Plots allow to distribute two or more data sets over a 2D or even 3D space to show the relationship between these sets and the parameters on the plot. Charts vary from bar and line charts that show the relationship between elements over time to pie charts that demonstrate the components or proportions between the elements of one whole. The easiest way to show the development of one or several data sets is a chart. Here are the common types of data visualization techniques: Charts However, dashboards are not necessary to show a single or occasional data insight.ĭepending on these factors, you can choose different data visualization techniques and configure their features. In order to make a complex analysis, visualizations are compiled into dynamic and controllable dashboards equipped with different tools for visual data analytics (comparison, formatting, filtering, etc.). The goal of data visualization affects the way it is implemented. Depending on the rate of change, you may consider dynamic representation (steaming) or static data visualization techniques in data mining.

BASIC DATA VISUALIZATION SERIES

For example, financial results can be measured monthly or yearly, while time series and tracking data are changing constantly. There are various types of data, and each type has a different rate of change. On the contrary, to differentiate elements, you can use contrast colors. To emphasize a certain figure, for example, significant profit growth, you can use the shades of one color on the chart and highlight the highest value with the brightest one. You can use different data visualization approaches and read data depending on the context. In turn, bar charts work well for comparative analysis. To show the relationship between two elements, scatter plots are often used. For example, if it’s time-series metrics, you will use line charts to show the dynamics in many cases. The type of data you are dealing with will determine the tactics. On the other hand, if data insights are intended for researchers and experienced decision-makers who regularly work with data, you can and often have to go beyond simple charts. For example, fitness mobile app users who browse through their progress can easily work with uncomplicated visualizations. It’s important to adjust data representation to the specific target audience.

5 factors that influence data visualization choices:

BASIC DATA VISUALIZATION FULL

Vice versa, poorly selected tactics won't let you unlock the full potential of data or even make it irrelevant. Choosing the right technique and its setup is often the only way to make data understandable. To translate and present complex data and relations in a simple way, data analysts use different methods of data visualization - charts, diagrams, maps, etc. Visualization is the first step to make sense of data. What determines data visualization choices

BASIC DATA VISUALIZATION HOW TO

We will talk about the most widely-used tools for data visualization and give a few pro tips on how to combine data visualizations into effective dashboards. In this article, we review major data visualization instruments and name the key factors that influence the choice of visualization techniques and tools. The ever-growing volume of data and its importance for business make data visualization an essential part of business strategy for many companies. How to Use Data Visualization Techniques and Tools for Business

Basic data visualization