Engineering and Science (Data Visualization)

^{Image source Pixabay.com}

Changing information to visual context is known as data visualization. It is a means of translating maps or graphs for easy understanding by identifying a partner, trends, or outliers of large data. Data visualization is a branch in data sciences that put together large data. These large data are then processed and visualized for conclusions to be made. Data visualization is needed in every sector, which is used to gather information and display results in human understanding.

^{Image source Flickr.com}

Why is data visualization important?

• Data visualization can absorb a large amount of information.
• Data visualization helps to display efficient results within a short period.
• Data visualization gives understandable information to its audiences
• Data visualization eliminates the need for data scientists.
• Data visualization helps in distributing information share insight with everyone.
• Data visualization gives the ability to quickly search, with fewer mistakes.

Data visualization and big data

As organization projects data is growing, Data visualization is needed by the organization to be able to gather the data they have to manage. The use of machine learning is increasing as these organizations find it difficult to work with huge amounts of data. Data visualization helps to give understanding within fewer times of these big data. Big data visualization is more than normal data visualization such as histograms, pie charts, and graphs. When we are talking of Big data visualization, they are the need for powerful computers to collect the raw data, process and display it for human understanding.

Examples of data visualization

I'm sure we are familiar with the most common visualization technique (Microsoft Excel spreadsheet), which is used to transform data into a table, pie chart, or bar graph. We are still using it today for the little data we gather around. Other techniques now available are

• Infographics
• Bubble clouds
• Bullet graphs
• Heat maps
• Time-series charts

Some Popular techniques

• Line Charts: Line charts are used to display how variables change over time on a chart. It is the most commonly used in organizations today.

• Area Chart: Area chart is used to display multiple values in a time series. The data is collected at an equal interval of time, it can be seen as a variation of a line chart.

• Scatter plot: This technique takes the form of the x and y-axis to display the relationship between the two axes. Dots are used to represent the data points between the two variables.

• Treemaps: These techniques make use of rectangle sizes for each category to show hierarchical data in a nested format. The percentages are used for each category to compare the different parts they represent.

Data visualization is used to represent large data in the simplest and most understandable means for us humans. We have seen some of the techniques we are applying in data visualization in our little corners. It helps us analyze a large amount of data, and give efficient meaning to it. I will use this opportunity to call on administrators in most of the communities on the steemit platform to make use of pie charts and bars to display the data gathered from their communities.

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