There has been a lot of increase in the information and knowledge revolution, which has allowed one to ensure that the key aspects of the research and strategy building can gather a piece of more meaningful information and insights. This information is generally stored in a data warehouse which can later be used for business intelligence purpose. There are many several definitions and views which will allow one to get the right subsets.
Data mining
Data mining is a nothing but a systematic and sequential process which will help one identify and discover the hidden patterns in the very large dataset. Data mining is a process which involves the extraction of machine learning, statistics and databases. It is also known to work as knowledge discovery in the databases. Data mining specialists can usually allow one to have the right algorithms sorted; they are data analysts with much more extensive knowledge of inductive learning. It is responsible for the extraction for all the meaningful patterns and structure in the data. This helps mining the data much more easier as it allows one to have the right data pattern. The E-commerce sector can make use of data mining which will allow one to display the options on the screen.
Data Analysis
The superset of data mining that involves the extraction, cleaning, transforming, modelling, visualisation has to uncover many meaningful and useful information which can be used to derive conclusion allowing to one to make the right decisions. It requires one to have the right knowledge statistics, mathematics, subject knowledge and AI machine learning. Data analysis allows one to have the right exploratory, description and text analytic methods. A data analyst usually can be used by a single person. The Job profile involves the preparations of raw data which can be used in cleansing and transforming. The responsibility for the development models can vary from hypothesis to hypothesis. The output of data analysis is a verified hypothesis or insight into the data.
Data mining and analysis are still sometimes used interchangeably. This is also considering when the team takes up a challenge to make the right decision. This allows one to have a unique identity with major data mining and data analysis differences.
- Data mining helps discover a pattern which is hidden in a large dataset, whereas data analysis gives insights about a test by reviewing the dataset.
- Data mining is one of the activities which involves data analysis. Data analysis is a set of activities which takes care of the collection, preparations and modelling of the data.
- Data mining studies are structured in a subset, whereas data analysis can be done structure, semi surfaced or unstructured.
- The goal of data mining is to ensure that there is more usable data where the data analysis helps in providing the hypothesis of taking the right business decisions.