The potential of “big data,” the massive explosion of sources of information from sensors, smart devices, and all other devices connected to the Internet, is probably under-appreciated in ...

Identify big data or large, distributed systems. Know when and when not to use big data. Practice software engineering fundamentals. Create an application that uses rest collaboration, event ...

Big data is a moving target, and it comes in waves: before the dust from each wave has settled, new waves in data processing paradigms rise. Streaming, aka real-time / unbounded data processing ...

Overcoming Big Data obstacles Make sure that the identified use case is appropriate for a Big Data solution. Highly structured and transaction-oriented data may be better served by a traditional DBMS.

One day, corporations awoke to the fact that having data was not the same thing as having believable data. They awoke to discover the meaning of 'data integrity.' That was the day the enterprise data ...

Specialization: Software Architecture for Big Data Instructor: Tyson Gern and Mike Barinek Prior knowledge needed: Software engineering or big data experience View on Coursera Learning Outcomes ...

In its announcement on 2/18, MapR made a strong statement about its vision of the right product to support use of big data in the business world. MapR’s product is its platform, a set of ...

Securing big data systems is a new challenge for enterprise information security teams. This article offers advice for building security in when designing enterprise big data architectures ...

While both approaches support analytics, albeit in different order, ETL dates to the 1970s and is often used interchangeably with data integration.