Overview of Data Aggregation Tool
- Web scraping is a powerful data sourcing technique that leverages tools and frameworks to scrape data from the public domain.
- The scraped data can be aggregated and transformed into the meaning format and loaded into any database in a structured format.
- Web scraping can be done using custom programming or by leveraging many tools.
- Web scraping is a powerful data extraction mechanism that will accelerate your data journey to annotate them for better grouping, build a cognitive intelligence layer on top of it using Artificial Intelligence & ML, and leverage data visualization tools for better insights.
- Data Scraping: Easily scrape data from target websites and organize them into a structured data format for annotation and consumption via services.
- Building Data Warehouse: Gathering transition data from multiple heterogeneous sources for using it for Sentiment Analysis, getting meaningful insights and visualization.
- Data as Service: Leverage cloud services like AWS or Microsoft Azure or GCP to expose scraped and aggregated data as a service to be consumed by applications on demand.
- Data Labeling: Label and annotate the data to build machine learning models and cognitive intelligence.
Data Aggregation – 3 Stage Model
Web scraping will be done to scrape and transfer data from a website to a new datastore. The data fetched from multiple source systems may be structured or unstructured data. Then the extracted data will be cleaned up and validated before loading it into a common database.
Stage 1: Extract
This is the first stage of ETL, where data can be fetched from different data repositories of the company.
The data extracted may be unstructured, non-understandable data format.
Stage 2: Transform
In the second stage, the extracted data will be validated, normalized, and homogenized, and converted into structured data.
Stage 3: Load
In the final stage of ETL, the normalized data will be loaded into a common database repository.
Data Aggregation – 4 Best Tools