Online analytical processing (OLAP) databases are purpose-built for handling analytical queries. Analytical queries run on online transaction-processing (OLTP) databases often take a long time to ...

Data warehouse systems have been at the center of many big data initiatives going as far back as the 1980s. Today companies from leading cloud hyperscalers such as Amazon Web Services (Redshift) and ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

According to Gartner, Inc., CIOs need to familiarize themselves with nine key trends in data warehousing and how they will impact the cost-benefit balance of technology deployed to deliver business ...

The true measure of an effective data warehouse is how much key business stakeholders trust the data that is stored within. To achieve certain levels of data trustworthiness, data quality strategies ...

The digitization of the modern business enterprise has created a seemingly never-ending stream of raw data. Gleaning actionable nuggets of information from terabytes upon terabytes of data requires ...

Essentially, a data warehouse is an analytic database, usually relational, that is created from two or more data sources, typically to store historical data, which may have a scale of petabytes. Data ...

More than 400 million terabytes of digital data are generated every day, according to market researcher Statista, including data created, captured, copied and consumed worldwide. By 2028 the total ...