What is computational and data science?

Computational and Data Scientists develop mathematical models, quantitative analysis techniques, and use computers to analyse and solve scientific real-world problems. 

Computational Science is the practice of creating validated models to gain a better understanding of a system's behaviour. Computational science is defined by the use of numerical algorithms. Some of the applications of computational science are listed below.

Applications for computational science:

• Predictive computational science
• Urban complex systems
• Computational finance
• Computational biology
• Complex systems theory
• Computational science in engineering

Data Science is defined as the art of generating insight, knowledge, and predictions from datasets using methods. Data science has 5 stages.

1. Capture: Data collection, data entry, signal reception, and data extraction are all steps in the data collection process. This stage entails collecting both structured and unstructured data.
    
2. Maintain: Data Warehousing, Data Cleansing, Data Staging, Data Processing, and Data Architecture are all aspects of data management. This stage entails taking raw data and converting it into a usable format.
    
3. Process: Data mining, clustering/classification, data modelling, and data summarization are all examples of data processing techniques. Data scientists examine the prepared data for patterns, ranges, and biases to determine its usefulness in predictive analysis.
    
4. Analyze: Exploratory/Confirmatory, Predictive Analysis, Regression, Text Mining, and Qualitative Analysis are all examples of exploratory/confirmatory analysis. This is the meat of the life cycle. This stage entails running various analyses on the data.
    
5. Communicate: Data reporting, data visualisation, business intelligence, and decision making are all aspects of data management. Analysts prepare the analyses in easily readable forms such as charts, graphs, and reports in this final step.