In the early 2000s, manufacturers asked, “How can we collect more data?” The industry resoundingly responded. Today, manufacturers collect unprecedented amounts of data, causing many to remember the ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. When it comes to data, today’s CIOs are being pulled in all directions. They’re asked to ...

Handling large amounts of data is a prerequisite of digital transformation, and key to this are the concepts of data lakes and data warehouses, as well as data hubs and data marts. In this article, we ...

There's a lot of fact, fiction and confusion surrounding data lakes. Not so much with my fellow chief technology officers (CTOs), but perhaps at the chief executive officer (CXO) level. It's not ...

Many enterprises are moving towards use of data lakes to help in managing increasing amounts of information. Such large repositories allow organisations to gather and store structured and unstructured ...

Both data warehouses and data lakes offer robust options for ensuring that data is well-managed and prepped for today’s analytics requirements. However, the two environments have distinctly different ...

Data continues to grow in importance for customer insights, projecting trends, and training artificial intelligence (AI) or machine learning (ML) algorithms. In a quest to fully encompass all data ...

The move towards an entirely data-driven business ecosystem has been underway for a while, but it hasn’t always gone smoothly. Although 96% of companies said that they saw success from data and AI ...

Ingesting large volumes of disparate data can yield a rich source of information — but it's also a recipe for data chaos. Use these tips to improve data quality as your data lake grows. Image: ...

Databricks announced today two significant additions to its Unified Data Analytics Platform: Delta Engine, a high-performance query engine on cloud data lakes, and Redash, an open-source dashboarding ...

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 ...