Graph analytics, which is an analytics alternative that uses an abstraction called a graph model. The simplicity of this model allows for rapidly absorbing and connecting large volumes of data from many sources in ways that finesse limitations of the source structures (or lack thereof, of course). Graph analytics is an alternative to the traditional data warehouse model as a framework for absorbing both structured and unstructured data from various sources to enable analysts to probe the data in an undirected manner.
Big data analytics systems should enable a platform that can support different analytics techniques that can be adapted in ways that help solve a variety of challenging problems. This suggests that these systems are high performance, elastic distributed data environments that enable the use of creative algorithms to exploit variant modes of data management in ways that differ from the traditional batch-oriented approach of traditional approaches to data warehousing.
We are using cookies to provide statistics that help us to improve your experience of our site. You can choose to use the site without cookies. However, by continuing to use the site without changing your settings, you are agreeing to our use of cookies.
Complete your membership listing and tell others about your interests, experience and qualifications with a Personal Profile page.
Your Personal Profile page is missing information about your experience and qualifications that other members would find interesting. Click here to update.
Login / Join Us
Please login to your DSF account for access to member only information and services. If you are not a member but have an interest in Data science, machine learning and AI, join us today.
02 May 2019 10:16:05 AM