A data warehouse is defined as a central repository that allows enterprises to store and consolidate business data extracted from multiple source systems for the task of historical and trend ...

Srinivasa Sridhar Kavikondala is a seasoned technical architect specializing in data warehousing and cloud solutions, based ...

Oracle CEO Larry Ellison today introduced the company's first hardware products, a joint effort with Hewlett-Packard, to re-architect large database and storage configurations and gain whopping ...

Experts joined DBTA's webinar, Top Trends in Modern Data Architecture for 2024, to examine how the evolving world of data architecture can be harnessed to successfully meet growing demands amid a ...

Organizations that really want to take advantage of a higher performance, more agile and lower cost data warehouse architecture, should implement master data management (MDM) to improve data quality.

In the ongoing debate about where companies ought to store data they want to analyze – in a data warehouses or in data lake — Databricks today unveiled a third way. With SQL Analytics, Databricks is ...

A fast, no-fuss data warehouse as a service, Snowflake scales dynamically to give you the performance you need exactly when you need it ...

The data lakehouse – it’s not a summer retreat for over-worked database administrators (DBAs) or data scientists, it’s a concept that tries to bridge the gap between the data warehouse and ...

Oh goodness, non-relevant un-automated badly warehoused cloudy big data in a Brexit style maelstrom of democratized openness. Wasn’t cloud computing supposed to make things easier? Yes, but not ...

Nearly every data warehouse ecosystem has attempted to manage master data within its data warehouse architecture, but has focused on mastering data after transactions occur. This approach does little ...