Introduction to Data Science
Introduction to Data Science
Data Science is the study of a large quantity of data, which involves extracting meaningful data(knowledge and insights) from raw, structured, and unstructured data. Extracting meaningful data from large amounts requires data processing, which can be done using statistical techniques and algorithms, scientific techniques, different technologies, etc. It uses various tools and techniques to extract meaningful data from raw data.
Properties of Data
Data can be understood as a collection or set of values, observations, or measurements. These values can represent various types of information, including qualitative and quantitative variables. Data is measured, collected, reported, and analyzed, after which it can be visualized using graphs or images.
- Amenability of use: Data are meant to be used as a base for arriving at definitive conclusions.
- Clarity: Data are a crystallized presentation. Without clarity, the meaning desired to be communicated will remain hidden.
- Accuracy: Data should be real, complete, and accurate.
- Essence: Large quantities of data are collected and must be Compressed and refined.
- Aggregation: Aggregation is cumulating or adding up.
- Compression: Large amounts of data are always compressed to a manageable size to make them more meaningful. data
- Refinement: Data require processing or refinement. When refined, they can lead to conclusions or even generalizations. Conclusions can be drawn only when data are processed or refined.
