Data visualization is crucial for making educated decisions as the business sector relies more and more on data. Data’s rising volume and pace make it impossible to comprehend without abstraction or visual depiction. Furthermore, data that are non-statistical, such as organization processes or customer journeys, are difficult to interpret and repair without visualization.

Data Visualisation has therefore become crucial for businesses to make data more accessible, understandable, and usable in decision-making. Data visualization is the source of business intelligence.

Is data Visualization so important?

Data visualization is a powerful tool that uses statistical visuals, information graphics, charts, and other approaches to clearly and effectively show complex data. Facts visualization facilitates user comprehension and reasoning about facts and evidence by encoding numerical data with dots, lines, or bars. Tables are used to search specific measurements, while charts display data patterns or correlations for more Variables.

Thanks to the Internet and increasing modern technologies, transforming data into understandable images is now possible for everyone. One con is the inclination to prioritize convenience above quality. Transforming the spreadsheet cells into charts can provide merely passable or useless charts since it fails to convey the fundamental notion. As a result, before clicking and viewing data, it is critical to evaluate your aim and objectives.

Creating an Insightful and Profitable Visualization Strategy

To make effective charts, it takes more than just understanding visual grammar rules. It is crucial to understand when to use and how to handle the key and colours; relying solely on rules can result in a lack of strategy in the chart-making process, similar to planning a marketing campaign without a plan. Instead, effective chart-making demands acknowledging a sequence of tasks requiring varying degrees of plotting, resources, & expertise.

Analyzing the purpose of data or information is critical before generating a visualization. Is it conceptual? Is the visualization meant to make a statement or discovery? By answering these questions, you may identify the sources and gears required to build a successful visualization that meets your objectives. This method allows you to choose the most effective visualization style for conveying your message to your audience. As a result, good chart creation begins with careful planning and a clear knowledge of your visualization objectives.

Also Read:  Domo for Dummies: A Guide to Creating Powerful Data Visualizations with Domo

Tips and Tricks!

Here are some surprising yet effective Data Visualization techniques that experts have emphasized and accepted:

Source: merkle.com (Image for representation only)

Art of Omission

The skill of omission should be treasured. You should emphasize what is vital and exclude what isn’t. This will assist in avoiding clutter and allow your audience to focus on the important issues.

Colors should be chosen with Caution.

Colors may be used to highlight the information, while incorrect use can conceal it. Choose easy colors on the eyes and provide a clear contrast between different data points.

Eliminating  Gauges

Although speedometers and gauges have been widely used in dashboards, newer visualization techniques that take up less space are now available. It’s recommended to consider using an easier visualization method instead of gauges.

Begin at zero

To prevent misinterpretation and ensure correct understanding of the scale, it is recommended to always start the horizontal axis of a bar chart at zero.

Display the distinction

You may highlight the differences if you wish to compare the two series. This will assist your readers in comprehending the significant areas of comparison and emphasize the value of the facts.

Pies

Pie charts may be colorful and visually appealing but are not always the best choice for displaying data. It is important to evaluate the relevance of a pie chart to the data being presented and use it only when appropriate.

Highlight what is relevantly essential

Maintain a neutral dashboard and highlight just what is relevant, such as the present location or a critical metric. This will allow the audience to concentrate on the essential points and comprehend the value of the material.

Graphs from a different perspective

Consider using a horizontal bar graph when dealing with labels or hierarchy in your data. It is recommended to explore various types of charts and graphs to effectively highlight your information.

Here are some tools that can be used to implement the mentioned Data Visualization techniques:

Art of Omission:

a. Tableau – Allows users to selectively show or hide elements of a visualization.

b. Power BI – Offers various filters and slicers to customize and refine visualizations.

Colors should be chosen with Caution:

a. ColorBrewer – Provides color schemes that are colorblind-safe and printer-friendly.

b. Adobe Color – Allows users to create, save, and export color schemes.

Eliminating Gauges:

a. D3.js – A JavaScript library that can create custom visualizations and eliminate gauges.

b. Plotly – Offers various visualization types that can replace gauges, such as bullet charts.

Begin at zero:

a. Microsoft Excel – Allows users to manually set axis limits and customize the display of data.

b. ggplot2 – A popular R package that includes the ability to set axis limits and control the display of data.

Display the distinction:

a. QlikView – Offers various charts and tables to highlight the difference between data points.

b. Highcharts – Provides a wide range of customizable chart types to display distinctions.

Pies:

a. Google Charts – Provides a variety of pie chart customization options.

b. Chart.js – A JavaScript library that can create customizable pie charts.

Highlight what is relevantly essential:

a. Plotly – Provides a range of charts and tables that can be customized to highlight essential data points.

b. SAP Analytics Cloud – Offers features to highlight the important aspects of a visualization, such as conditional formatting and alerts.

Graphs from a different perspective:

a. Matplotlib – A popular Python library that provides a wide range of visualization types, including 3D graphs.

b. Vega-Lite – A declarative language for creating interactive visualizations, including custom perspectives.

Excel:

Excel is a widely used spreadsheet program that also offers basic data visualization capabilities. It can be used to create charts, graphs, and other visualizations, and can be a good option for simple visualizations or data exploration.

Wrapping Up

Being able to visualise data in the data-driven world of today is essential for making successful decisions. The ability to master data visualisation is a skill that is attainable through the use of a variety of tricks and tips, and it can significantly improve one’s capacity to comprehend and analyse complex data. Anyone can become a better analyst and improve their data visualisation skills by adhering to best practices like selecting the proper visualisations, structuring data in a meaningful way, and using colour and design effectively. With these strategies in mind, people and organisations can use data visualisation to generate insight, wise choices, and significant outcomes.

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Behavior Driven Development (BDD) is another test development process derived from TDD. In BDD, testers create tests for the user behaviors. The Gherkin file is used for creating scenarios for end-to-end tests.

TDD vs. BDD Comparison

What is Gherkin?

Gherkin is a simple structured language that helps to create behavior-based tests using simple English, file can be read and understood by anyone in the software development team.

Gherkin is mostly used to define the tests to cover the end-to-end workflow. Writing scenarios in an independent/standalone way without creating dependency on each other is important.

Each scenario in a Gherkin file will be considered a standalone test.

Gherkin files should be saved with a .feature extension to automate the scenarios.

Many assume that writing feature files in the Gherkin language is easy, but it’s not. Though Gherkin uses simple syntax (Given, When, And, Then…), it has to be used wisely to define meaningful steps. It’s moreover like an art.

Preparing Gherkin is not just documentation work. A person involved in preparing Gherkin files has more responsibility as they are converting system requirements into system behaviors from a user perspective.

Best practices in preparing gherkin feature files.

Avoid lengthy descriptions.

We must keep the Title & Description short; when the description is long, the readers may skip the lengthy description.

Scenario Background.

The scenario Background adds some context to each scenario. It is like a pre-requisite for scenario execution. Though writing Background is not mandatory like scenarios and steps, they can throw more context on the test and reduce the repetition of steps as they can act as pre-condition.

If there is no Background detail to add to any scenario, we may add some additional detail that are required or help to complete executing the scenario.

For Example:

• Test Data,
• Experiment files used for this test,
• Database connection,
• Other interface connectivity,
• Etc.…

Scenario.

Prepare scenarios using clear statements as we document the requirements in user behavior format. Project stakeholders can access these documents for various reasons, such as to read and understand the requirement, to automate the tester to develop a script, and for future reference.

Project members have different levels of application understanding. We must consider this and prepare Gherkin files from lay man’s perspective.

Preparing scenarios at a high level (or) using too many statements is not recommended. Prepare only apt scenarios and steps.

The scenario is high level.

Scenario with too many statements.

Scenario with apt statements.

Pass accurate input parameters.

Always mention the accurate values in the input parameters, sometimes, the results may vary, and our scripts will fail. By passing accurate values, we can save much time, such as failure analysis, script rework, re-execution, etc.

Scenario Outline?

Using “Scenario Outline” is always good, especially when testing with N input parameters of similar workflow.

There are many advantages when we use the syntax “Scenario Outline.”

1. We can pass many parameter values using the same parameter key.
2. The number of statements in the Gherkin file will reduce.
3. Readability is good.
4. Easy to maintain when there is an update or rework.

Using “Scenario” syntax:

Using “Scenario Outline” syntax:

Avoid Technical Terms.

Do not use any technical term (or) coding language in the Gherkin file, as it may not be understood by a non-technical person in the project.

Use the present tense

There is no such rule to prepare a Gherkin file only with the present tense, but I would suggest using the present tense wherever it is possible. It will keep the readers engaged with the application.

Statements with past/future tense.

Statements with the present tense.

Maintain the same naming convention.

We should maintain the same naming convention in all the scenarios inside the Gherkin file. Also, try to maintain all the Gherkin files in the project.

Add more negative scenarios.

This is a common rule applicable to any kind of testing. It is always good to have more negative scenarios in your test scripts. It helps us to validate the application, especially in negative situations. Like how effectively the application is designed, developed, and built to handle unexpected user behaviors.

For instance, does the application show a proper error message to users in unexpected workflow, how quickly can an application recover, any data loss, etc.

Alignment

We must ensure that all the lines are properly aligned inside a Gherkin file.

Always prepare the Gherkin file perfectly, as this will be the first impression to others about the document and its quality and content. It creates interest in the readers and helps them to complete reading quickly.

Avoid Spelling Mistakes

Not a major mistake, but spelling mistakes should be avoided in the Gherkin file. It will create a bad impression on the readers. Keep the content of the file simple without mistakes.

Make sure we enable the spell-check option while working on Gherkin files.
Sometimes spelling mistakes may not be highlighted in red lines, which means we haven’t installed the spell check extension and must install and enable it.

For Ex: “Code Spell Checker” & “Spell Right” extensions.

Process-related best practices can also be considered in the project.

• Gherkin file review/approval process.
• Collect all the Gherkin files and place them in a common repository.
• The Gherkin file should be updated whenever there is a change.
• Provide access rights to everyone in the project.
• Read-only access to the Gherkin folder (except leads/manager) 
• Maintain proper folder structure.
• Maintain version controlling.
• Periodic backup and maintenance.
• We can involve the functional team in preparing Gherkin files if the automation team fully engages with scripting work.

Conclusion

In conclusion, following best practices in preparing Gherkin feature files is crucial for effective and efficient software development. By adhering to guidelines such as writing clear and concise scenarios, using descriptive language, organizing scenarios with proper structure, and involving stakeholders in the process, teams can improve collaboration, facilitate test automation, and ensure the delivery of high-quality software. Implementing these best practices empowers teams to create feature files that are easily understood, maintainable, and valuable assets throughout the software development lifecycle.

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