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How data visualization helps in data analytics

Data visualization refers to representing data in forms that can be visually perceived. In layman’s terms, it is the process of making data presentable so that the human mind can relate to it easily and understand it quickly. In many cases, data visualization helps in the decision-making and presentation of complex processes and procedures in an easy-to-understand manner. With that said, let’s look at how data visualization helps with data analytics!

Data Visualization, Why Does it Matter?

Data visualization is not just a visual representation of data but can be a powerful tool to present complex information easily and quickly. When used with care, they are easy to understand even by those with little to no experience or knowledge in dealing with numbers and formulas. Because they help find trends faster and easier than traditional methods, they also make it easier for everyone involved – from analysts, managers, and decision-makers – to come up with informed conclusions. In short, they are now considered an essential part of any comprehensive data-analysis process. To learn more about data visualization, visit Aftros.

Data Visualization and The Big Picture

We’re all inundated with a never-ending torrent of digital information these days. And yet, at times, it can be hard to make sense of it all. Without some extra context, raw statistics aren’t very useful. It’s far more helpful to visualize those numbers instead and often easier to digest. Visualizations help us identify important patterns and trends that might otherwise have been easily overlooked. But when you have so much information flowing into your company regularly, how do you decide what should be visualized? Big data tools like Panoply come in handy; they allow you to quickly create meaningful graphs and charts using massive amounts of information collected from your business processes.

Doing Data Visualization Right

So you want to make a good-looking chart, huh? Well, it takes more than PowerPoint or Excel. A lot more. To create an effective chart that communicates well with your audience, you have to think about your graphic’s actual content. Your audience and their knowledge level. Your goal for using data visualization. It would help if you also had: A detailed understanding of how each aspect (color, fonts, size, etc.) will affect its outcome: good design skills and attention to detail.

Relevance is the Key to Effective Data Visualization

What are you trying to say with your chart? You must make sure your chart is relevant to your topic. Are you trying to show an overall trend or break it into different categories? Regardless of what you’re trying to show, be clear about it and articulate it before beginning. Focus on Creating Visual Clarity: It’s tempting when we’re working with a lot of information to try and put as much as possible onto a graph so that there’s no room for any other interpretation. However, this creates visual clutter and often leads people down the wrong road. Instead of including every single bit of information available, identify a few key pieces and focus on making them as clear as possible instead of overcrowding them.

Choosing the Right Type of Chart for Your Goals

90% of people said they believed that visual data analytics was easier to understand in a survey. When you’re putting together your company’s sales reports or creating a PowerPoint presentation, it pays to use charts and graphs to illustrate what’s happening with sales and profits. This infographic will give you an overview of all types of charts available and tips on how best to use them. Whether you’re trying to boost sales or find patterns in your performance numbers, understanding which type of chart will be most effective for your purposes can help ensure success.

Do’s and Don’ts of Data Visualization

Data visualization is becoming increasingly important to businesses worldwide as they seek to communicate effectively. It has become a vital part of many processes—from scientific research to marketing and sales. Data visualization can help you determine what your customers are looking for, where your sales come from, and how well different teams are doing. Using other means, you can use it to make sense of large amounts of data that would otherwise be difficult or impossible to understand. A lack of data visualization skills could hamper your company’s growth. So you must know how it works and can apply it as necessary.

Here are some do’s and don’ts to keep in mind when working with data visualization.

  • Do – Use visual elements to tell a story about your data.
  • Don’t – Make any false assumptions about patterns or trends based on your visualizations alone.
  • Do – Use charts, graphs, and infographics to convey information quickly and clearly.
  • Don’t – Assume that every chart will work best with every dataset (different charts are used for different types of information).
  • Do – Always look at old data visualizations in new ways: Check out how others have presented similar datasets before creating something new.
  • Don’t – Take anything at face value: Always verify any conclusions you draw by analyzing your data independently.

To create an infographic, we need two things – text and images. Let’s add both of them now into our markdown file, which we created above just after

Final Words

Once you have all of your data processed, it’s time to visualize it. Data visualization is the process of representing your findings visually. You can show results that may be difficult to explain in words, or you can also tell a story with graphics that add meaning and clarity to your results. For example, let’s say we were interested in finding out if our hypothetical new medicine was able to affect people with Chronic Obstructive Pulmonary Disease (COPD). Because COPD tends to cause difficulty breathing, limiting how much walking patients could do. We would want to see if our drug helped them walk further after taking it for four weeks.

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