Business Intelligence, Data Quality, Data Transformation and OLAP

Self-Serve Data Preparation Doesn’t Mean Traditional ETL is Dead!

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse

Data Warehouse OLAP Data Governance Optimization

Database vs. Data Warehouse: What’s the Difference?

Jet Global

MAY 28, 2019

Unlike a database, a data warehouse’s architecture is built for getting the data out, and not just through technical expertise, but for common users like management, executives, finance professionals, and other staff. A data warehouse is typically used by companies with a high level of data diversity or analytical requirements.

Data Warehouse

Data Warehouse Reporting Business Intelligence Sales

Data Leaders Brief

Self-Serve Data Preparation Doesn’t Mean Traditional ETL is Dead!

Database vs. Data Warehouse: What’s the Difference?

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