Data Science is defined as the entire process of extracting actionable insights from raw data, which includes concepts such as statistical analysis, data analysis, machine learning algorithms, data modelling, data preprocessing, and so on.
With tremendous growth in the field of the Internet of Things (IoT), resulting in the generation of 90% of the data generated today. Every day, 2.5 quintillion bytes of data are generated, and this number is increasing due to the growth of IoT.
This information is derived from a variety of sources, like
- Sensors used in shopping malls to collect information from shoppers Posts on social media platforms
- Phone-captured digital photos and videos
- E-commerce purchase transaction.
All such types of statistics are known as Big Data.
Process of Data Science
Raw data from various sources is gathered to explain the business problem.
Data modelling is performed using various statistical analyses and machine learning approaches to obtain the best solutions that best explain the business problem. Data science provides actionable insights that can be used to solve business problems.
Obtaining Raw Data
Raw data or information can be gathered from various sources, APIs in the case of social media platforms, websites, etc.
Modelling Data
The data scientists preprocess and clean the data using statistical analysis and machine learning techniques. Relevant features such as sentiment scores, user demographics, and engagement metrics are extracted. The information is then transformed into a structured format that can be analyzed.
Insights That Can Be Used
To gain insights, data scientists analyze structured data. They look for patterns, trends, and correlations in the data. These insights provide actionable information to the company on how to improve its brand perception and engagement strategies.
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