data visualization and its need and usage
- 2. Introduction Your data is only as good as your ability to understand and communicate it. You need to be able to understand and effectively communicate the story behind those numbers. The best way to tell a story with your data is by visualizing it using a graph, a chart, or some other visualization. Data visualization will help you uncover patterns, correlations, and outliers. It’ll help you communicate insights to your boss, your team, or your company. It’ll help you make the data-backed decisions you need to be great at your job. It’s critical that you choose the right method of visualizing your data for any given data set. You would never choose a pie chart to show trends over time, for example; and you would never choose a line graph to show parts of a whole. But it’s more than that: If your data is misrepresented or presented ineffectively, you and your team will lose out on key insights and understandings – which hurts both your message and your reputation.
- 3. What is data visualization Data visualization refers to showcasing data, numbers, and statistics through images and charts. When you display data visually, you’ll be able to more easily tease out meaningful patterns from a set of otherwise indecipherable numbers, and it makes it easier to draw conclusions and make informed decisions.
- 4. Data visualization is especially helpful when you’re presenting data to others. It’s much easier for people to understand data when it’s presented visually – which makes it easier to make your point or persuade someone, too. Marketers can use data visualization to showcase the results of a campaign; scientists can use it to predict illness outbreaks; farmers can use it to map out agricultural trends. You can also use data visualization to display part-to-whole data, ranking, correlation, geographical distribution, deviation, timelines, and scale. The purpose of data visualization can be to simplify and showcase results or to explore trends and try to discover something new within a set of data. What is data visualization
- 5. A brief history of data visualization For centuries, data visualization has helped those in the fields of mathematics, epidemiology, business, science, and marketing to draw conclusions, discover patterns, and make decisions informed by the facts rather than "gut feelings." One of the first examples of data visualization dates back to the eighteenth century. 1769 1864 1885 1901 2006 Johann Lambert used charts to catalogue water evaporation experiments. He was among the first recorded scientists to use scientific visualization to describe and analyze data. The nineteenth century marked the beginning of modern graphics. One notable example came from John Snow, who used plot points on a map for each case of cholera in London. He concluded that a water pump in an area called Broad Street might be the source of the outbreak, due to the distribution of cases. This is a prime example of a distribution visualization. Etienne Jules Marey invented the first iteration of what is now the blood pressure cuff, which he called the sphygmograph. It was a portable device that could record the human pulse visually on paper. This was one of the first ways that blood pressure was measured visually. Arthur Bowley created this time-series graph mapping out the value of European goods sold over successive ten year periods. Al Gore’s film An Inconvenient Truth used data visualization to persuade audiences of the dangers of global warming. You can take a look at more of the visualizations in this visualization library, but watching the film itself shows the power of animated data visualization as well as the impact that data can have on persuading an audience.
- 6. Why is data visualization important? Data visualization is important in identifying trends, answering questions, proving theories, and -- if you’re creating them for a business -- in showcasing your brand. When you visualize your data, you can more easily see numbers in context and understand how they relate to one another. When it comes to processing information, we are wired to comprehend images much faster and more easily than text. According to Disruptive Learning, we process visuals 60,000 times faster than text. What’s more, visuals are far more memorable than text is. The same research study found that after three days, test subjects retained 10-20% of written or spoken information and a whopping 6 5 % of visual information.
- 7. Why Data Visualization is Important to Showcase Metrics and Reports Data visualization improves the impact and recall of your message or argument. Have you ever attended a presentation where someone else’s presentation stood out to you thanks to its clear representation of data? We’re willing to bet many of you had. We said it before, and we’ll say it again: Accurate visualization of data can make or break a business presentation. Let’s take a look at an example. Below, you’ll see two versions of the same slide from a presentation deck. The first, with the white background, is the actual presentation slide; the second is a re-imagining of that slide from Professional Presentation Designer Emiland de Cubber.
- 9. Comprehensive. It doesn’t leave questions unanswered, and it provides enough information for viewers to get the big picture and any appropriate context. In short, it tells the full story. Current. The world changes quickly, so your data needs to be one or two years old at most – unless it’s on a topic that hasn’t changed in a long time. Use your discretion here. Reliable. You’ve verified that the source you chose was relevant, legitimate, and as unbiased as possible. You’ve asked yourself who collected the research and whether they have credentials, when it was last updated, and whether the organization hosting the information has a purpose or agenda that could make the data biased.
- 10. Where and how are you getting your data? If you don’t have any data yet, you’ll need to think carefully about where you’re getting it. Are you gathering yourself, or are you getting it from someone else? If you’re gathering it yourself, be sure you’re using the right methodology to write and launch your surveys. To learn how to use online surveys effectively, download our free ebook, How to Use Online Surveys in Your Marketing. If you’re collecting your own data, you’ll need to make sure you collect enough of it for the results to be statistically significant. Here’s a refresher on statistical significance from a marketing standpoint if you need one. If you’re sourcing your data from a third party, it’s very, very important that it’s coming from a reliable source. What makes a good data source? A good data source is: Original. It comes from a primary source. If the data you find is on Wikipedia or in a news article, track down the original data so you can spot any potential flaws, low sample sizes, or biased questionnaires.
- 11. Data types, relationships, and visualization formats 4 Data Types 1)Quantitative Quantitative data can be counted or measured, and all values are numerical. 2) Discrete Discrete data is numerical data with a finite number of possible values. (For example, the number of employees in an office.) 3) Continuous Continuous data is measured and has a value that lies within a range. (For example, rainfall in a year.) 4) Categorical Categorical data can be sorted according to group or category. (For example, types of products sold.)
- 12. Data visualization tools There are many different tools and data visualization software that you can use at varying levels of expertise to analyze and present data. Here are a few favorites: • M icrosoft Excel This is the most common tool for data visualization. Excel allows you to sort and analyze data, then create data visualizations using the chart wizard. To learn more about using Excel, check out these resources here and here. • Statista Statista is a database of studies, statistics, and forecasts that provides market data for presentations. • HubS pot Research This free website allows you to make your own presentation using the latest marketing and sales statistics and charts. • Google Trends Google Trends is a free tool from Google that shows search history of certain topics and keywords over time. You can create custom trend graphs of keywords by region, country, or area and select any time range. • SocialMention SocialMention lets you monitor user-generated content mentions online. This is a great tool to measure and show brand awareness and engagement.
- 13. Data visualization tools • Infogram Infogram is a tool to create infographics and charts. It is ideal for those with little design experience to create and customize infographics. Alternatively, you can download some simple, pre-made infographics templates here. • Photoshop & Illustrator For more advanced designers, you can use Adobe Photoshop and Adobe Illustrator to create beautiful and more elaborate data visualizations. These are a great option to create long form infographics and brand visualizations. • Canva Canva is a really easy-to-use free tool with a new charts feature for creating simple pie charts, bar graphs, and more in any sized template. This is a great option for creating presentations, infographics, and social images. • Tableau Tableau offers sophisticated data visualization and integrations with data visualization software like Excel, which helps you easily make raw data into beautiful visuals. • Google Charts or Google Sheets Google Charts lets you embed graphs and charts onto a web page. It is an API tool that lets you create custom graphs and charts with the option to animate them for a more dynamic visualization. Google Sheets (Google’s version of PowerPoint) is a good option for creating simple charts and graphs like you would in Excel.