Data science is an interdisciplinary field, including statistics, computer science, and information science, that uses scientific methods and principles to analyze data in order to gain new knowledge. Data scientists generally work with big data, including processed data and raw data, to perform a data analysis. These analyses can then be presented as a high-level data visualization to organizations or can go in depth when being presented to relevant subject matter experts.
Data science relies on proper storage and retrieval of information, such as in a data warehouse. By data warehousing data, organizations can securely store present and historical data in one place, which is generally considered a key component of business intelligence. Data analysts can access this stored data and then choose an appropriate analysis method, such as statistical modeling or clustering, to arrive at conclusions based on the information provided. Data engineering can be used as part of the analysis to find practical applications for the data, such as which items to put on sale or how best to organize products next to each other.
Data science relies heavily on computer science, particularly artificial intelligence (AI) and machine learning (ML), to help arrive at data-driven conclusions. Through different programming languages, data scientists can enable data analysis at every step of the data ingestion process. Analyses can be automated across data acquisition, data classification, data storage, and data protection to make sure the data is arriving at the appropriate location, and that all trends and conclusions being drawn from the data are updated in real time.
Behavioral analysis is one aspect of data science that utilizes data in order to figure out how people are likely to behave based on past trends. This analysis enables organizations to implement plans that allow them to engage with customers in the most effective ways and can help them figure out how best to market their services in the future. This type of analysis is not just limited to retail businesses, but can also be used to predict crimes, or anticipate voting patterns in local, state, and federal elections.