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Raw Data to Visualization: Top 5 data visualization techniques for beginners

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5 Data Visualisation techniques for beginners

In the changing world, Machine Learning and Artificial Intelligence play a crucial role in providing profitable business solutions to companies. They help the companies to make smart decisions with the help of the analysis conducted from the data provided. With Data Science And Analytics, the companies can analyse the data and provide profitable solutions.

With the rising demand for Data Science, you need to gain experience for years before becoming an expert. With courses from recognised universities like IIM Nagpur and Shiv Nadar, one can gain the expertise and move towards making a successful career in Data Science.

5 Data visualisations techniques for beginners

Before understanding the five data visualisation techniques that can help beginners, let us understand Data Visualisation. Data Visualisation is the technique of creating a graphical representation of information. This helps in providing the data in a systematic way that would help the Data Scientists to analyse and provide conclusions. 

Several types of data visualisations can provide beneficial for Data Science for Business. Let us look at the top 5 Data visualisations techniques that would help beginners in their careers.

  • Pie Chart – The most common way of representing information and can be used in many applications. Pie charts are easy to understand, and it is helpful to the audience that requires a more detailed level of understanding. The information explained in the pie chart gives a clear picture and helps in taking proper business decisions by the executive members of the company. Data Science and Analytics use pie charts to explain the information to the audience.
  • Bar graph – Just like a pie chart, a Bar graph is an easy way to analyse information. In it, the data is represented in the x and y-axis. One axis represents the categories for comparison, whereas the other axis represents the value of the measurements for comparison. The analysis is done as per the height of the bar for each group. This gives a more detailed understanding of the information. Even though it is simple to understand, sometimes it can be an issue when there are too many categories. 
  • Gantt Chart – Gantt Chart is the most commonly used data visualisation technique in project management. The chart displays the project’s entire timeline with the details. The time interval is displayed on the horizontal axis, whereas the tasks are reflected on the vertical axis. This is highly helpful in understanding the project timeline and would give a better picture of when the project would be ready for the market. With machine learning and artificial intelligence, the company can predict the outcome of the project’s timeline.
  • Heat Map – The heat map provides information through different colours. This data visualisation technique in Data Science communicates through different colours that make the audience easier to understand. The heat map can be used by major retail store chains to understand at what time their stores get maximum footfalls. The day can be mentioned on the vertical axis, and the timings can be mentioned on the horizontal axis. By putting the colours on the boxes, the team can identify the market trends and can come up with new strategies to improve their business.
  • Area Chart – The area chart is a slight variation from the line graph, where the portion beneath the line is coloured to represent the data. This chart is used to show multiple changes in over quantities in a particular period. Explaining the information is easy for the audience, and it provides information in a more detailed manner.

There are several Data Science Degrees, but pursuing Data Science from recognised universities would give the candidate an extra edge over others. The one-year Data Science for Business Excellence and Innovation course from IIM Nagpur and the 8-month Certificate in Data Science and Analytics for Business from Shiv Nadar University equips the students with AI, Python, ML, Simul8, NumPy, TensorFlow, and others. These programmes focus on industry exposure and provide the students with real-life business problems. They provide the students with the skill to understand and analyse the data through Data Science and Analytics. Undergoing the course from these universities would play an essential role in shaping the career of the freshers. 

Conclusion

The Data visualisation techniques are indispensable to analysing the data. The companies heavily depend on it, and the data scientists should be able to work on these techniques to provide the company with the required information. Learn more about Data Science by pursuing the course from IIM Nagpur and Shiv Nadar University.

FAQs

  • Can a fresher become a Data Scientist?

Yes, a fresher can become a data scientist. Some courses lookout for experienced professionals, and some seek freshers and experienced candidates.

  • Is there a demand for Data Scientists in India?

With the dynamic change in markets, the use of data to analyse information plays a crucial role in reaping benefits for any company. So, companies in India are looking out for Data Scientists with handsome salary packages. 

  • What is a Data Science course?

Data Science is a course that helps extract information from the data provided that would help solve complex business problems and provide financial benefits to the company.

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