Reading Time: 3 minutesReal-world big data use cases have moved beyond “possibilities” to multiple use patterns including analytics and low-cost archival storage of large datasets. In all cases, big data is thought of in an ENTERPRISE sense, even if big data analytics that is performed…
Reading Time: 2 minutesWhile Big Data Analytics has become all the rage over the past few years, another technology also has entered the mainstream: Data Virtualization. Data Virtualization is the process of abstracting different data sources through a single data access layer which…
Reading Time: 4 minutesMost companies have inadvertently locked away the value of their enterprise data assets, because they can rarely harness the right information at the right time. When they finally do access information, it is often inaccurate, incomplete or unavailable. This is…
Reading Time: 2 minutesData virtualization benefits impact on both the business and IT. It delivers value in a relatively short period and keeps paying back over time. From a business perspective, getting integrated information faster has resulted in numerous benefits including better customer…
Reading Time: 2 minutesData virtualization is being used in everything from small projects that are in need of quick data access, as part of bigger application or data warehousing project, as an enterprise-wide semantic or common data layer or any combination thereof. The…
Reading Time: 5 minutesDisclaimer: The author felt compelled to share some ideas that emerged at a Buddhist Vegan restaurant in Palo Alto, CA after a conversation on big data and data virtualization with analysts from a top CIO membership organization. The author claims…
Reading Time: 4 minutesCaching is one of the most important capabilities of a Data Virtualization platform to provide the right combination of high performance, low latency of information, minimum source impact, and reducing cost of needless data replication. In fact, the options for caching and…
