Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.Data science encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis. Analytic applications and data scientists can then review the results to uncover patterns and enable business leaders to draw informed insights
The most important things to learn in Data Science are:Mathematical concepts such as linear algebra, probabilities, and distributions. Statistical concepts such as descriptive and inferential statistics. Programming languages such as python, R, and SAS.
The four types of data analysis are:
- Descriptive Analysis. What is it ?
- Diagnostic Analysis. What happened?
- Predictive Analysis. What will happen?
- Prescriptive Analysis. How to make it happen
The four components of Data Science include:
- Data Strategy.
- Data Engineering.
- Data Analysis and Models.
- Data Visualization and Operationalization.
Six Qualities of a Great Data Scientist
Statistical thinking. Data scientists are professionals who turn data into information, so statistical know-how is at the forefront of our toolkit
Technical acumen. …
Multi-modal communication skills. …