Data Customization | Web Scraping Tool | ScrapeStorm

ScrapeStorm is a powerful, no-programming, easy-to-use artificial intelligence web scraping tool.

Introduction

Data customization is the process of transforming, modifying, and adjusting the raw data collected for specific conditions and purposes. Examples include unifying data formats, eliminating duplicate data, adding or removing specific fields, filtering, and standardizing. Through this process, data is adjusted so that users and systems can use it effectively.

Applicable Scene

Customizing data in an easily analyzable format can improve the accuracy of reports and dashboards in BI tools. Segment and customize customer data to help optimize targeted advertising and personalized offers. Integrating data from different systems and platforms requires formatting and schema mapping. Feature engineering and scaling are performed during data preprocessing for model training.

Pros: Optimizing data for specific purposes can improve the accuracy of analysis and reporting. Efficient data processing can be achieved by removing unnecessary data and noise and extracting only necessary data. Integrate data between different systems and databases and convert them into a common format to ensure data compatibility between different sources. Customizing data enables you to provide personalized services and products, improving customer satisfaction.

Cons: The customization process requires specialized skills and tools, which incurs labor costs and tool implementation costs. Data customization increases system complexity and leads to management and maintenance difficulties. If you have large amounts of data or complex customization requirements, processing time may make real-time data utilization difficult. Extra care must be taken, as incorrect customization or conversion may result in data loss or incorrect formatting.

Legend

1. A Custom Data Analytics Dashboard.

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Reference Link

https://learn.microsoft.com/en-us/dynamics365/customer-service/use/datamodel-overview?tabs=historicaldatamodelcustomization

https://www.ibm.com/docs/en/i/7.4?topic=services-customizing-data-collections

https://help.crisp.chat/en/article/what-is-custom-data-and-why-is-it-powerful-43jgi3/