Palantir and Snowflake are data warehousing tools that offer unique methods of interacting with large, non-relational data sets. While Palantir uses private operating system models, Snowflake offers a ...

Salesforce has more than 150,000 customers, making it one of the most popular and most powerful customer relationship management (CRM) platforms on the market. Organizations need a 360-degree view of ...

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 ...

Data Warehousing is the storage of big data. Data mining is the analysis of the collected data in order to find trends in the collected data.

Today’s businesses understand the power of data. It surrounds every aspect of their operations from marketing and sales to new product design, and even the onboarding of new employees. Captur­ing, ...

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, ...

This piece explores cloud and multi-cloud object storage and data management options recently announced by MinIO (with Snowflake), Commvault and Retrospect (part of StorCentric). Let’s see what these ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Enterprises are fast adopting data ...

More and more companies are using AI or planning to use it. However, 95% of projects fail. The reasons for this are ...

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 ...

Warehouse-native access is emerging as the fastest, safest path to unified customer intelligence. It isn't without its challenges.

I talk to a lot of different businesses about their data, and, without fail, some form of the same question always comes up: “What is the most common reason you see data warehouse projects failing?” ...