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Reading Time: 3 minutes Some still think it makes sense to compare ETL tools with data virtualization servers. Let me be clear, it really doesn’t. Unquestionably, both tool categories belong to the class of data integration tools, like data replication tools, data wrangling tools,…
Reading Time: 6 minutes Ok, forgive the hyperbole in the title since data virtualization doesn’t actually have magic powers to keep you safe from getting ticketed by the police. However, in one specific series of incidents that I recently encountered which did involve getting…
Reading Time: 4 minutes Allow me to introduce the (fictitious) Advanced Banking Corporation, or ABC for short. It may be advanced in name, but its IT systems are anything but. ABC will be our constant companion as we explore all three scenarios for data…
Reading Time: 3 minutes Some still see data virtualization as an alternative technology to ETL. For them it’s nothing more than another style of data integration. However, data virtualization is much more. Data virtualization is about abstraction. It’s about data consumers being decoupled from…
Reading Time: 3 minutes 2018 is exactly thirty years since I published the first data warehouse architecture. The core concepts of the architecture remain strong and viable. However, the evolution of both business needs and technology solutions over the intervening decades has led to…
Reading Time: 6 minutes In the previous article we reviewed the architectural elements of the virtual data lake, dug deeper into its technical implications. In this post, we will review the architectural elements of the virtual data lake, and will discuss why a virtual…
Reading Time: 4 minutes Believe it or not we are now over 25 years into building data warehouses and many companies around the world have very well-established systems supporting query, reporting and analysis of historical master and transaction data that has been captured from…
Reading Time: 2 minutes Savvy organizations know that business growth and success are intrinsically linked with an effective strategy for managing data. But as the big data momentum builds, more questions are raised. In this post, I’ll answer five of the most important ones….
Reading Time: 6 minutes The amount of data a company can manage these days is huge, but making use of these data for analytics and decision-making can be hard and expensive using traditional approaches.Traditional architectures like data warehouses and data lakes rely on storing…
Reading Time: 7 minutes Many organizations have made it a high priority to implement a data virtualization solution. This makes sense, since traditional data warehouses can no longer keep pace with the explosive growth in data volumes and user queries. The logical data warehouse…
