Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping ...

I work at a startup and our data is very messy at the moment, as you might imagine. We have a few product level transactional databases, but no central database to store it all in a useful way for ...

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Amilcar has 10 years of FinTech, blockchain, ...

Bharath Gowda, Databricks' VP of product marketing, briefed ZDNet on the news by phone. He said Data Ingestion Network charter members include Fivetran, Qlik (with its Data Integration product, ...

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 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 ...

The true measure of an effective data warehouse is how much key business stakeholders trust the data that is stored within. To achieve certain levels of data trustworthiness, data quality strategies ...

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?” ...

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 ...