Question

In what circumstances is data visualization better than using text explanations and tables of numeric data? In what situations is it worse? Justify your reasoning.

Answer 1

Answer :

Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends and outliers in large data sets. The term is often used interchangeably with others, including information graphics, information visualization and statistical graphics.

Importance of data visualization

Data visualization provides a quick and effective way to communicate information in a universal manner using visual information. The practice can also help businesses identify which factors affect customer behavior; pinpoint areas that need to be improved or need more attention; make data more memorable for stakeholders; understand when and where to place specific products; and predict sales volumes.

Data Visualization Uses:

• Newsletters: Generally shorter than a blog post, but longer than a social media post, newsletters are perfect for data visualization. You can include some data visualization in an email newsletter to feature your company’s unique findings, statistics, or status.
• White Papers & eBooks: Include data visualization to help prove the points you make in the document to influence your readers.
• Annual Reports: Whether you’re collecting your year’s greatest hits for your internal team, or wanting to share your wins with your clients, you can create an illustrated annual report, complete with data visualization, to provide an overview of the past year, success stories, and analysis.
  Trying to create more data-driven narratives ? Check out our post, “Storytelling Through Data Visualization”.

Infographics : Data visualization plus Text Application Uses:

• Blog Posts: Because blog posts are written for a specific purpose, publish your infographic on your blog, or segment it into pieces for supporting the text in your post.
• Case Studies: Paired with a study of a particular context, an infographic can provide engaging visuals and succinctly summarize a lengthy report, offering valuable insights to your readers.
• Marketing Content: If you want to build greater awareness of your brand, consider distributing your infographic across your channels, by separating it into short sections. Post these on social as thumbnails. Increased social sharing can result in widespread awareness of your brand.

Other benefits of data visualization include:

• the ability to absorb information quickly, improve insights and make faster decisions;
• an increased understanding of the next steps that must be taken to improve the organization;
• an improved ability to maintain the audience's interest with information they can understand;
• an easy distribution of information that increases the opportunity to share insights with everyone involved;
• eliminate the need for data scientists since data is more accessible and understandable; and
• an increased ability to act on findings quickly and, therefore, achieve success with greater speed and less mistakes.

Examples of data visualization

In the early days of visualization, the most common visualization technique was using a Microsoft Excel spreadsheet to transform the information into a table, bar graph or pie chart. While these visualization methods are still commonly used, more intricate techniques are now available, including:

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

Common data visualization use cases : Common use cases for data visualization include:

Sales and marketing. Research from the media agency Magna predicts that half of all global advertising dollars will be spent online by 2020. As a result, marketing teams must pay close attention to their sources of web traffic and how their web properties generate revenue. Data visualization makes it easy to see traffic trends over time as a result of marketing efforts.

Politics. A common use of data visualization in politics is a geographic map that displays the party each state or district voted for.

Healthcare. Healthcare professionals frequently use choropleth maps to visualize important health data. A choropleth map displays divided geographical areas or regions that are assigned a certain color in relation to a numeric variable. Choropleth maps allow professionals to see how a variable, such as the mortality rate of heart disease, changes across specific territories.

Scientists. Scientific visualization, sometimes referred to in shorthand as SciVis, allows scientists and researchers to gain greater insight from their experimental data than ever before.

Finance. Finance professionals must track the performance of their investment decisions when choosing to buy or sell an asset. Candlestick charts are used as trading tools and help finance professionals analyze price movements over time, displaying important information, such as securities, derivatives, currencies, stocks, bonds and commodities. By analyzing how the price has changed over time, data analysts and finance professionals can detect trends.

Logistics. Shipping companies can use visualization tools to determine the best global shipping routes.

Data scientists and researchers. Visualizations built by data scientists are typically for the scientist's own use, or for presenting the information to a select audience. The visual representations are built using visualization libraries of the chosen programming languages and tools. Data scientists and researchers frequently use open source programming languages -- such as Python -- or proprietary tools designed for complex data analysis. The data visualization performed by these data scientists and researchers helps them understand data sets and identify patterns and trends that would have otherwise gone unnoticed.

When to Visualize Data : Use visuals (graphs, maps) for spatial tasks, when the answer to the viewer’s question lies in

• the shape of the overall data (e.g. patterns, trends, exceptions)
• relationships among whole sets of values (distribution, part-to-whole, correlation)
  
  AND the scale is not broken

In what situations is it worse? : When NOT to Visualize Data

Don’t use a visual for symbolic tasks. Use tables for symbolic tasks. Stephen Few agrees that tables are better than graphs when the answer to the viewer’s question lies in

• Individual values
• Comparing selective pairs of values and not entire series
• A precise value
• Both summary and detail values
• More than one unit of measure
  
  OR the scale is broken: a lot of small numbers and a few very large numbers, or vice versa.

It can be explained as follows: Tables work especially well when numbers differ by orders of magnitude so that no scale suffices in plotting them. Consider this set of numbers: 20; 400; 160,000; and 25,600,000,000. A chart will lose the detail of low figures if it tries to reach the high ones without breaking the scale. If you must break the scale, then just use a table, because a chart with a broken scale is no longer a true picture of the numbers.