eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Organizations can no longer afford to rely on a traditional data warehouse solution to support new business intelligence (BI) requirements along with their existing BI workloads. The rigid development ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Today’s enterprise challenges demand near real-time access to data. While that seems to be a must, the application ecosystem continues to present a growing array of data persistence options, such as ...

AtScale is a data virtualization provider for analytics. What this means is that AtScale provides an abstraction layer that enables its users to access the underlying data stores it supports in a ...

Data warehouse virtualization startup Datometry Inc. today said it has raised $17 million in new funding to accelerate go-to-market activities with its partners Microsoft Azure, Amazon Web Services ...

Business today moves faster than ever—and it’s driven by massive amounts of data to inform, enhance and accelerate decisions that can make or break a company. Data virtualization has played a pivotal ...

To fit into modern analytics ecosystems, legacy data warehouses must evolve—both architecturally and technologically—to deliver the agility, scalability, and flexibility that business need to thrive ...

The data warehouse architecture and the data lake design pattern have converged to form a new, richer data architecture, a new report says, and both have already gone mainstream in the cloud.

The "data" part of the terms "data lake," "data warehouse," and "database" is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere. But should they be stored in a ...

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 ...