Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A data warehouse is defined as a central repository that allows ...

Stop spending on the ever-growing list of data technologies, and simplify your architecture with a single Streaming Data Warehouse Who has the most pivotal role in your company? Is it your CEO? Is it ...

Without the right processes and tools, it’s easy for a digital analyst to spend more time pulling and organizing data than reporting their findings and delivering meaningful analyses. What can ...

With the majority of DBTA subscribers reporting the existence of budgets for modernizing their data platforms, the widespread demand for greater scalability and agility becomes a difficult task to ...

Snowflake's approach unifies structured and unstructured data analysis within its platform by treating documents as queryable ...

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 data ...

Enterprise data warehouses, or EDWs, are unified databases for all historical data across an enterprise, optimized for analytics. These days, organizations implementing data warehouses often consider ...

Data lakes and data warehouses are two of the most popular forms of data storage and processing platforms, both of which can be employed to improve a business’s use of information. However, these ...

Data lakes and data warehouses are achieving a measure of success in modern data architectures, but the emergence of the data lakehouse offers new challenges and opportunities for database ...

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 the data ...