Data engineers position is slightly different of analytical positions. Instead of mathematics, statistics and advanced analytics skills, learning Spark for data engineers will be focus on topics: ...

For data engineers looking to leverage Apache Spark™'s immense growth to build faster and more reliable data pipelines, Databricks is happy to provide The Data Engineer's Guide to Apache Spark. This ...

In particular, since image data can be stored in the file system, it is advantageous to handle large-scale images without data loss.” Although the focus here is on computation and memory, disk ...

The company says its data management expertise spans the entire data lifecycle, from ingestion to visualisation. Stoop writes as follows… While the concept of data engineering isn’t new, its ...

Data engineering teams already use Airflow for AI-related tasks like tracking the path to production, validating data lineage and ensuring trust in results. Now, the focus is on extending that ...

2. Variety: Handling Structured And Unstructured Data. AI relies on diverse data types: structured transactional logs, semi-structured JSON and unstructured images, videos and social posts.

Mukul Garg is the Head of Support Engineering at PubNub, which powers apps for virtual work, play, learning and health. In my journey through data engineering, one of the most remarkable shifts I ...