Data Engineer @Quant... • 1y
The Data engineering life cycle has the following 5 stages Generation: This is where data is created. Think of it as information being born. It can come from various sources like e-commerce sites, weather sensors, or even your favourite video games scores. Storage: This stage is all about saving data in a secure place, such as big databases or cloud storage, so it can be easily accessed later. Ingestion: Ingestion is like gathering all the data from different places and putting it into one big bucket. This stage involves taking data from various sources and moving it into a central storage system where it can be processed. Transformation: It involves cleaning and organizing the data, removing errors, joining multiple tables, removing duplicates, applying business rules, and converting it into a useful format. Serving Data: This stage ensures that data is easy to access and use, whether it's for creating reports, running apps, or making decisions.
Founder | Agentic AI... • 2m
Most AI projects don’t fail because of models. They fail because data never flows properly. Without reliable data movement, even the smartest AI system becomes useless infrastructure. Everything begins with pipelines. They quietly power modern ana
See MoreLooking at objective... • 2y
IDEA : AI Training Data generator A Developer Platform which is much specify for AI-ML field to achieve various tasks like Analysis, Generation and Segmentation of real time data across data like text, image, audio, video that requires heavy and hig
See MoreHey I am on Medial • 1y
Breakthrough discovery could charge your dead phone in 60 seconds and your car in 10 minutes • Scientists at CU Boulder have made a groundbreaking discovery in energy storage, potentially enabling phones to charge in 60 seconds and electric cars in
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