Data Analytics have now captured lots of things. It is a very vast technology. It is the process of collecting the data according to the requirements and sort it based on decision making. The data is collected from different resources such as question answering, customer reviews, the data may also be collected from sensors, cameras. The data can be in any format images, audio, video, text.
Once collection and processing are done the data is been cleaned, where the duplicates and errors are removed. The main is identifying the inaccuracy of data, quality of data, and also duplication of data. Complex data can also be sorted in data mining, very the data is sorted into a tabular format, and after processing and cleaning the data, analysis of the data is done.
Data processing is done by storing the data into rows and column format, for doing analysis. It provides difficult information for healthcare. It increases the efficiency and performance of the system. This helps the customer to work easily.
There are different types of data cleaning which depend on the type of data, that could be phone numbers, email address. Such a text checker can be used to check spelling mistakes.
There are 4 types of data analytics:
Data mining is important to process in data analytics, where the data is extracted from unstructured data. The data may be text, complex database, or sensor data. The main aim is to extract, transform, and load data. This technique converts raw data into a useable format, after that storage and analysis are done.
Data warehousing is another important phase in data analytics. In this technique, designing and implementation of a database are done, which allows easy access to data mining. It generally does collect and managing SQL databases.
Applications of data analytics:
- Manage risk.
- Fraud and risk detection.
- Customer Interaction.