Existing distributed computing frameworks are failing to keep a lid on the growing computational, memory and even energy costs resulting from the constantly expanding volume Big Data for anything ...

The heterogeneity of the big data landscape is characterized not only by the distributed nature of its most prominent technologies, but also by their underlying architectures. Organizations are ...

The course covers basic principles of systems for distributed processing of big data including distributed file systems; distributed computation models such as Mapreduce, resilient distributed ...

In today’s data landscape, a distributed architecture is driven by the need for real-time insights, compliance, and the scalability provided by cloud computing, with organizations increasingly ...

Who is the Graduate Certificate in Big Data Analytics program for? Drexel College of Computing & Informatics' Post-Baccalaureate/Graduate Certificate in Big Data Analytics, a sub-field of Data Science ...

One retailer I worked with reduced recommendation engine training time by 90% by switching from a relational database to Apache Spark, leveraging in-memory distributed computing. 3. Real-Time Data ...

The four roots of DeFi — artificial intelligence, big data, cloud and distributed ledger technology — are explained in this guide.

With the exponential growth in enterprise data from a proliferation of Internet of Things (IoT) devices, cameras, sensors, and other devices, companies are increasingly turning to edge computing ...

The course enables students to learn about the principles and gain hands-on experience in working with the state of the art big data computing technologies such as Apache Spark, a general engine for ...