Data ingestion is the process of collecting and importing raw data from various sources (Database, API, Data Streaming services) into a system for processing and analysis, and can be performed in batch and realtime ingestion. The goal is to gather raw data that can be processed and analyzed.
Used for building Data Pipeline
Challenges
- Data Quality: Ensuring that the ingested data is accurate, complete, and consistent.
- Scalability: Handling large volumes of data efficiently as the data sources grow.
- Latency: Minimizing the delay between data generation and processing, especially in real-time scenarios.
Use Cases:
- Data ingestion is used in various applications, including: business intelligence, Machine Learning
Related to: