Question

1.What is Data visualization and what are the major applications of real-life scenarios and how it works in details.

2.What is the Latest development of Data visualization (popularity, new techniques, current applications)

3.What is the usual knowledge gap between major people perspective and the knowledge required to apply Data visualization?

Answer 1

1. What is Data visualization and what are the major applications of real-life scenarios and how it works in details.

Data visualization is the presentation of quantitative information in a graphical form. In other words, data visualizations transform large and small datasets into visuals that are easy for the human brain to understand and process. With data visualization, you'll take the concept a step further by using technology to use charts and graphs for more detail.

Today quite ever, organizations use data visualizations, and data tools, to ask better questions and make better decisions. New user-friendly software programs have made it easy to find out more about your company and make better data-driven business decisions. The strong emphasis on performance metrics, data dashboards shows the importance of measuring and monitoring company data. Common quantitative information measured by businesses includes units or product sold, revenue by quarter, department expenses, employee stats and company market share.

In order to craft a good data visualization, you need to start with clean data that is well sourced and complete. Once your data is ready to visualize, you need to pick the right chart. After selecting the chart type, you need to design and customize your visualization to your liking. Make it as simple as it can be. There are chances of adding elements that distract from the data.

2. What is the Latest development of Data visualization (popularity, new techniques, current applications)

Data visualizations and knowledge graphics (infographics) has already become an important tool for today’s mainstream media. Data journalism is hot at the moment and journalists consistently believe quality visualization tools to assist them tell stories about the planet around us. Many well-respected institutions have fully embraced data-driven news including The NY Times, The Guardian, The Washington Post, Bloomberg, The Huffington Post and the Economist also. Marketers also benefit greatly from the mixture of quality data and emotional storytelling. Good marketers make data-driven decisions on a day to day, but sharing with their customers requires a special approach - one that touches both intelligently and emotionally. Data visualizations help marketers share their message using statistics and heart.

Major Techniques

Charts

The easiest way to show the development of one or several data sets is a chart. Charts vary from bar and line charts that show relationship between elements over time to pie charts that demonstrate the components or proportions between the elements of one whole.

Plots

Plots permit to distribute or more statistics units over a 2D or maybe 3-d space to reveal the connection between these units and the parameters on the plot. Plots also vary: scatter and bubble plots are the most traditional. Though whilst it comes to big records, analysts use field plots that enable to visualise the connection between massive volumes of different statistics.

Maps

Maps are widely-used in many industries. They allow to position elements on applicable gadgets and areas - geographical maps, constructing plans, internet site layouts, etc. Among the most popular map visualizations are heat maps, dot distribution maps, cartograms.

Diagrams & Matrices

Diagrams are majorly used to describe complex data relationships and links and include various types of data on one visualization. They can be hierarchical, multidimensional, tree-like. Whereas, a matrix is a big data visualization technique that allows to reflect the correlations between multiple & constantly updating data sets.

Data visualization tools

Tableu is one of the leaders in this field. Both newbies and professional analytics companies like Statista rely on this platform to create stories and derive meaning from their data. Among other popular data visualization tools in this category are easy-to-learn Visme, Fusioncharts with varied integration capabilities, free and open source Datawrapper and ZingChart for JavaScript and HTML5 charts.

Data visualization tools for coders

These tools enable not only data visualization, but also a certain level of data analytics.

Plotly is one of the most popular ones in this category. This visualization tool allows to create charts using R or Python, build custom data analytics web apps with Python, and even use and collaborate in rich open-source libraries for R, Python and JavaScript.

Sisense is another data visualization tool with full-stack analytics capabilities. This cloud-based platform has drag-and-drop interface.

IBM Watson Analytics This platform enables conversational data control alongside strong dashboard building and data reporting tools.

3. What is the usual knowledge gap between major people perspective and the knowledge required to apply Data visualization?

The concept of using pictures to understand data has been around for centuries, from maps and graphs in the 17th century to the invention of the pie chart in the early 1800's. It’s technology, however, that truly lit the fire under data visualization. Computers made it possible to process large amounts of data at lightning-fast speeds. Today, data visualization has become a rapidly evolving blend of science and art that is certain to change the corporate landscape over the next few years.

Although, to be a data analyst requires great knowledge of different front-end and back-end languages like JavaScript, Python, R and many others. Its not that only learning some particular languages will make you a good data analyst, you should know basic data analyzing techniques and tools. The conclusion is if you have a passion for data visualization, language barrier (as described above) can be easily encountered.