Add Raw Data parsing（PlatON）
Raw Data parsing refers to the process of analyzing unprocessed or preprocessed data to extract valuable information and insights. From a professional perspective, Raw Data parsing typically involves the following aspects:
- Data preprocessing: Before parsing Raw Data, preprocessing work such as data cleaning, data integration, and data conversion is often required. This includes removing duplicate data, filling in missing values, converting data formats, etc. for subsequent analysis.
- Data exploration: This stage involves preliminary exploration of data through statistical analysis, visualization, and other means, in order to understand the basic characteristics of the data, such as distribution, trend, outliers, etc.
- Feature engineering: Extracting or constructing useful features for model training from raw data. This may include extracting textual features, temporal features, numerical features, etc. from the data.
- Model: Use parsed data to construct predictive or statistical models. This may include training machine learning models such as regression models, classification models, clustering models, etc.
- Result interpretation: Explain the results of the model to understand how the model draws conclusions from the data. This requires analysts to have in-depth business knowledge and data comprehension abilities.
- Validation and optimization: Verify the accuracy of the model through cross validation A/B testing and other methods, and adjust and optimize the model based on the results.
- Report writing: Write the analysis results and insights into a report, usually including key findings, data visualization, conclusions, and recommendations.
In various industries, the application of Raw Data parsing is very extensive. For example, in the financial industry, market trends can be predicted by analyzing transaction data; In the medical industry, analyzing patient data can assist in diagnosis and treatment; In the marketing industry, marketing strategies can be optimized by analyzing consumer behavior data. Raw Data parsing is a complex process that requires interdisciplinary knowledge and skills, including statistics, computer science, business understanding, and data analysis.