Data analytics refers to the process of organizing, processing, analyzing, and mining massive amounts of collected data using various methods and technologies to extract valuable information and insights that can provide basis and support for decision-making.
Data analytics aims to discover the patterns, trends, and associations behind data to help companies and organizations optimize operations management, improve business efficiency, reduce costs, and enhance competitiveness.
The core tasks of data analytics include data cleansing, data organization, data visualization, data modeling, and data application. Data cleansing refers to the pre-processing of raw data, including the removal of duplicates, missing and outliers. Data organization is the categorization, sorting and integration of cleaned data for further analysis.
Data visualization is the presentation of data in the form of charts, graphs, etc., to facilitate an intuitive understanding of data distribution, relationships, and trends. Data modeling, on the other hand, is the in-depth analysis of data through the establishment of mathematical models in order to discover the patterns and trends. Data application is to apply the analysis results to actual business scenarios to provide support for decision-making.
Characteristics of data analysis:
1, large amount of data: with the development of Internet technology, the amount of data generated has grown exponentially, including but not limited to structured data and unstructured data, such as video, audio, pictures, etc..
2. Diverse data sources: Data comes from a variety of sources, including but not limited to social media, mobile devices, sensors, log files, and so on.
3, fast processing speed: traditional data processing methods have been unable to meet the requirements of real-time, so it is necessary to use new technical means, such as streaming computing, batch computing and other technologies.
4, diverse analysis methods: data analysis methods include statistical analysis, machine learning, deep learning and other methods, you can choose the appropriate method for analysis according to different needs.
5, wide range of application scenarios: data analysis can be applied to various fields, such as finance, healthcare, education, transportation, etc., which can help companies or organizations better understand user needs, optimize product design, improve operational efficiency, etc.
Reference: Baidu Encyclopedia-Data Analytics