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Reading Time: 6 minutesOk, 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: 3 minutesWith data becoming the brain food to the intelligence of every organization, regardless of size or sector, it has become crucial to harness this data to achieve the best results, make the most informed decisions and improve productivity. However, with…
Reading Time: 4 minutes2019 is the year of the data-driven organization. The more data an organization collects, the more insights they will have, right? Well no actually, it’s more about how you glean the insights from the data rather than how much data…
Reading Time: 3 minutesIn this article, I will discuss the complexity of data migration when transitioning to a new system, based on the traditional ways of working. I will explain why data virtualization can play a role in taking away this complexity, for…
Reading Time: 3 minutesPublic clouds and on-premises data centers can now be strategically connected via a strong hybrid architecture, simplifying data integration. If you are in the process of building a virtual data services layer across all of your disparate data sources in…
Reading Time: 3 minutesOrganizations are challenged by a complex mix of data sources, so they struggle to harness trusted, actionable insights in a timely manner. To more effectively keep up with business expectations, they need a nimble technology like data virtualization, which enables…
Reading Time: 2 minutesEver since 2015, when the price of oil dropped precipitously, oil and gas companies have had to find every opportunity to reduce expenses while maximizing every available revenue source. For Anadarko Petroleum Corporation, this meant transforming its analytics capabilities, which…
Reading Time: 3 minutesI have long been an advocate of integrating data quality techniques as a core component of an organization’s end-to-end data processes. When I began evangelizing data quality management about twenty years ago, the common practices for data quality involved post-processing…
Reading Time: 3 minutesWhen E.F. (Ted) Codd developed the relational model in the early 1970s, he had a dream. He wanted applications to be independent of the data storage and data access layer. Changes made to one should not lead to changes to…
Reading Time: 2 minutesThe current data-volume explosion can be traced back to a time when our society began to focus more on customers as individuals. We see ourselves as independent, unique people with free will, not bound by social conformity. Catering to that…
