What and Why of Data Visualisation?
Learn data, and you can tell stories that more people don’t even know about yet but are eager to hear. - Nathan Yau
To tell a story using data, Data visualisation can serve as a key.
Data Visualisation is the way of communicating the data or information visually. To communicate we can use different visuals such as charts, maps, images, icons, etc.
Data visualisation communicates the relationships in data. It is important because helps us to understand the complex raw data by allowing us to see the trends and patterns in data.
It is necessary to understand data visualization not only for data scientists or data analysts but also in any career whether you are in finance, tech, marketing, design, medicine, etc. This fact showcases the importance of data visualization.
Why do we need data visualization?
In the modern world of Data, where we have huge amounts of data, data visualization is important for analyzing massive amounts of information and make data-driven decisions. As most of the data sets are far too large to consume in their raw data format. Data visualisation helps us to find errors in data and allow us to clean the data .
How does the Human Brain respond to visuals?
Even if anyone is new to reading data in a chart we humans have already built-in capabilities to spotlight & dark colours, large & small shapes, groups and orientation of objects. These attributes what we called as pre-attentive attributes.
Visual analytics leverages our pre-attentive attributes. Visual cues human process automatically with sensory memory, Human mind is designed in such a way. We can notice and interpret these kinds of attributes quickly & without special effort.
How to be a well-educated data consumer or chart consumer?
The following three things should be considered -
- Know the elements of charts
Most charts we read and use can have the following common characteristics -
a) Quantitative axis- The axis which represents the measures in the data.
b) Tooltip- It gives more specific details about the data.
c) Mark- The term used to describe the visual representation in of the data like a bar is a mark in the bar chart.
d) Filter- The filter is used to view a specific subset of the data.
e) Legend- It is used to define what colours or shape in a chart represents.
f) Qualitative Axis- The axis which represents the fields(dimensions) or categories.
g) Labels- It represents what each mark represents.
2. Ask Questions
While reading charts and dashboards to get insights from data we should ask questions to ourselves. Some of the questions which serve as guides are-
a) What does this chart represent?
b) Does the chart or dashboard have a clear title or purpose?
c) Does this show any particular patterns or trends?
d) Does data have any outliers?
e) Are we able to answer all our queries with what we can see or we need more data?
f) Is it clear what has been measured and what the numbers represent?
g) Can we gather actionable and useful insights from the chart?
3. Watch out for misleading or confusing charts
Sometimes charts may be misleading and not proper so we should take care of it. Like some examples are -
a) Bar charts with axis not including zero(0).
b) Colour Confusion- Too many colours are used.
c) Wrong chart type used for representing the data.
How is data visualization used?
Data visualisation has many uses. There are various different ways that can be used for each type of visualisation. Some of the common ways in which data visualisation is used are-
- Changes over time- This is the most basic and important use of data visualisation. It helps us to see how the data trends and disruptions over time.
- In determining frequency- Data visualisation helps in determining how often a particular event happens or sometimes occur in different ranges.
- In determining correlations- It is quite tough to identify a relationship between two variables without a visual and it is quite important to be aware of relationships. So this is a good example of data visualisation.
- Analyzing value and risk- As determining complex values and risk involves many different parameters and it is almost impossible to see it accurately without the help of visual. So, data visualisation can be helpful in showing value & risk involving opportunities.
- Scheduling of tasks- Scheduling of a large number of tasks according to a timeline in the project is a very complex task. A Gantt chart easily solves that issue by clearly illustrating each task and determining how long a task will take to complete.
- Monitoring Goals and Results- Data visualisation can be used to determine the performance of sales, revenue, etc, over the quarterly or yearly goals. We can do this by using Key Performance Indicators.
- Aggregating Diverse Data- Data visualisation makes it easier to find insights in data coming from various sources.
Conclusion
Effective visualisation of data plays a very crucial role in making data-driven decisions. Without it, effective insights can be lost or would be difficult to gather. Data visualisation is a very important step in data analysis. Reports, Charts, Dashboards can help various organization working in different domains.
