Data Quality, Data Transformation, Data Warehouse 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

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

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?

Webinars

Stay Connected