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Business companies can already take the interactive visualization a step further by using technology to drill down into charts and graphs, interactionally changing how the data is seen and how it is processed. This is known as ‘data visualization’ – placing information (data) into a visual context, such as a map or graph. But why is data visualization so important nowadays?

1. Data visualization makes big and small data easier for the human brain to comprehend. Especially audiences with little knowledge in data analysis need data visualization because a visual report of information, such as maps or graphs, makes it easier to identify patterns and trends than looking through thousands of rows on a spreadsheet. It’s the way the human brain works!

2. Companies use data visualization to sort through mass amounts of data. Nowadays more and more companies use machine learning to collect great amounts of information, hence, visual representations permit them to sort out big data and data analyzation projects and explain big data to both the business owners and stakeholders.

3. In a complex project, data visualization gives data scientists a way to understand the data that has been collected. In this way, data analysts can monitor and adjust their processes to ensure it is accurately performing. Hence, it is much faster and easier to comprehend the results from complex algorithms in a visual format.

4. Data visualization is especially important in optimizing a website. Most often, it is used to analyze and implement strategies to improve a website’s SEO. Meaning that stakeholders that are not familiar with SEO can easily identify trends in the website’s content performance, keyword strategies, anchor text distribution, or geographic locations, and the quality of the backlinks.

5. Data visualization is important in any professional field in identifying relationships and patterns. It is extremely difficult to determine the relationship between two variables without a visualization, yet it is important to be aware of relationships in data. Some of the correlations will be obvious, but others will not. Identifying those relationships helps organizations focus on areas most likely to influence their most important goals.

6. It is too difficult and demanding to examine a network without a data representation. An example of analyzing a network with data visualization can be seen in market research. Marketing professionals need to know which audiences to target with their message, so they analyze the entire market to identify audience clusters, bridges between the clusters, influencers within clusters, and outliers.

7. Data visualization pinpoints and discovers emerging trends both in the business and in the market. It can give businesses an edge over the competition and ultimately improve the bottom line. It’s easy to spot outliers that affect product quality or customer turnover, and address issues before they become bigger problems.

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