Data Engineering System Architecture
Where Even the Smallest Byte Becomes a Superhero
Last updated
Where Even the Smallest Byte Becomes a Superhero
Last updated
The Hero Data Engineering System Architecture exemplifies a sophisticated and reliable framework, meticulously designed to ensure data accuracy, integrity, and accessibility within the Hero ecosystem. This advanced system incorporates several key components that collectively enhance the quality and reliability of our data, making it an invaluable resource for users.
ELT Automation: At the core of our system lies ELT (Extract, Load, Transform) Automation, driven by Apache Airflow. This component efficiently orchestrates the extraction of data from a wide array of reputable sources. These sources span social platforms like LinkedIn, Medium, Telegram, X (Twitter), YouTube, Facebook, Instagram, and Reddit, as well as market data providers like CoinMarketCap, DexTools.io, CoinPaprika, pitch decks, and much more. The extracted data is initially stored in a NoSQL database, providing flexibility and enabling preliminary validation and logical handling.
Data Transformation: The transformation phase ensures that the raw data is converted into structured formats through processes such as standardization and normalization. This step integrates data into a cohesive base model with associated connections, ensuring that the data is consistent and ready for further analysis and utilization.
Auditing & Research: Our system emphasizes thorough auditing and research to maintain the highest data standards. This phase involves both automated checks and manual reviews, ensuring the accuracy and completeness of the data. Tasks are meticulously tracked to monitor progress, enhancing the efficacy of data entry and research efforts. Asynchronous research and pre-rendering of data types are employed to validate changes, keeping the dataset current and reliable.
Data Warehouse: The final stage involves consolidating the processed data into a comprehensive Data Warehouse. This warehouse integrates SQL, NoSQL, and object storage solutions, offering a normalized dataset with RESTful API access, file system storage, and extensive documentation. This structured approach ensures that all data, whether structured or unstructured, is easily accessible and usable across the Hero ecosystem.
By leveraging this sophisticated architecture, the Hero Data Engineering System ensures that our data is not only highly reliable but also actionable and insightful. This multi-layered approach, combining automated processes with meticulous manual reviews, guarantees the highest standards of data integrity and security. The Hero ecosystem, powered by this advanced data system, provides users with unparalleled accuracy and confidence in their data-driven decisions.