Data Representation and Visualization
Data is often used by researchers, analysts, and scientists as symbols to represent people, events, things, and ideas. Data can be anything. From colors in a photograph to the notes in a musical composition.
What is Data representation?
Data representation and visualization online experts define data representation as the form in which data is stored, processed, and transmitted. The type of data at the disposal of the scientist will determine the type of representation or graph used.
- Categorical or categorized data are usually represented in the form of bar charts or pie graph
- The values for numerical data will affect the selection. For example, s smaller numerical data sets can be represented in a stack dot plot or the stem-and-leaf plot. These methods are adaptable and can be used to compare two data sets. On the other hand, large numerical data sets can be represented using histograms. Box plots are also appropriate for larger data sets.
Other representations that could be considered include a scatter plot which is useful for showing an association between two variables measured on the same cases.
What is data visualization?
Data visualization refers to the graphical representation of data using visual elements like maps, charts, and graphs. Tools used in data visualization offer an accessible way of seeing and understanding the trends, outliers, and patterns in data.
Data visualization technologies and tools come in quite handy in the world of big data. They have simplified ways of analyzing massive amounts of data and helping stakeholders make data-driven decisions.
Benefits of data visualization
The human eye can easily identify patterns and colors. One can easily differentiate red from blue, a square from a circle, and so forth. We can say that human culture is visual. This includes everything from advertisements on TV, art, movies, etc.
Data visualization is also a visual art meant to grab our interest and draw our attention towards the message. In an instance, we can see outliers and trends in a chart. You have probably stared at a massive spreadsheet and saw a trend. This is how effective visualization can be.
Almost every professional industry benefits from making data more understandable. For example, fields like finance, government, marketing, history, consumer goods, sports, education, service industries, and so on make informed decisions after understanding data. It is impossible to deny that there are real-life and practical applications that make visualization so prolific.
Data visualization is also ranked as one of the most useful professional skills to develop. You can leverage information better by conveying your points visually or through a dashboard or a slide deck. Today, skill-sets are being transformed to accommodate a data driven-world. This shows how important it is for professionals to make decisions using data visuals. The visuals can inform about the who, when, where, and how. The modern world needs someone who can cross between data analysis and visualization.
Common types of Data Visualization
- For time-series data
Line charts are the basic and mostly used visualization. They are used to show how one or more variables change over time.
An area chart is a variation of line charts used to display multiple values in a time-series. You can use an area chart to show cumulative changes in multiple variables over time.
- For ranking data
Bar charts are like line graphs, but use bars instead of dots to represent each data point. You should use bar chats when you need to compare multiple variables in a single timeframe or a single variable in a time-series.
These are stacked bar graphs used to display the complex social narrative of a population. It is best used when a researcher wants to show the distribution of a population.
- Part to Whole
Pie charts show parts of a whole in the form of a pie. So when do we use a pie chart? You can use a pie chart when you want to depict parts of a whole on a percentage basis. However, professionals recommend that you use other formats instead. This is because it is more difficult for the human eye to make sense of the data in this format. Line graphs or bar charts make more sense because they require low processing time.
Tree maps are tools used to display hierarchical data in a nested format. The categories percentage is directly proportional to the size of the rectangles. Tree maps are often used to compare expected and actual values for a single variable.
Other examples of data visualization tools include
- Scatter plots
- Box plots
- Bubble charts
- Heat maps
- Sankey diagram
- Network diagrams
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