Hepta Analytics

FEBRUARY 14, 2022

The data ingestion takes less time compared to ETL. It is also preferred when the use case has more diverse business intelligence. When the business intelligence needs change, they can go query the raw data again. ELT: source Data Lake vs Data Warehouse Data lake stores raw data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Let us first get a clear understanding of why Data Science is important. What is the need for Data Science?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

JUNE 14, 2023

Apache Spark – Labeled as a unified analytics engine for large scale data processing, many leverage this open source solution for streaming use cases, often in conjunction with Databricks. Data orchestration Airflow : Airflow is the most common data orchestrator used by data teams.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

MARCH 14, 2023

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59