Today databases and data warehouses are not only systems for reliable storage and processing of service information. One of the most attractive features of big data technologies is the cost of storing ...

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 ...

Since the 1990s, organisations have gathered, processed and analysed business information in data warehouses. The term “data warehouse” was introduced to the IT mainstream by American computer ...

Data warehouses have been at the center of data analytics systems within many businesses and organizations for years, going as far back as the 1980s. With the growing adoption of cloud, data warehouse ...

MySQL, the open source relational database that came to Oracle through the Sun Microsystems acquisition, originated as a relatively simple relational database that was known for one task: transaction ...

Introducing NoSQL database technologies into your data warehouse and analytics infrastructure can yield faster and more flexible insights. In this webinar, we explore how you can gain rapid insights ...

As we have pointed out before, large enterprises have to deal with a different kind of scale issue than the hyperscalers, and in many ways, the hyperscalers have it easier. The hyperscalers have ...

This week, Oracle announced a major extension of its cloud-based Autonomous Data Warehouse service that transforms it into an end-to-end offering with a heavy dose of self-service for business users.

If you’re looking for a quick and easy way to leverage ana­lytics focused on a specific topic, look no further. During his BLUEPRINT 4D session, Patrick Wheeler, product management, Oracle Database, ...