If you deal with machine data, chances are you're familiar with Splunk, a big data tool geared specifically for machine data. Splunk collects, indexes and correlates real-time data generated by ...

The Hadoop platform is designed to solve problems caused by massive amounts of data, especially data that contain a mixture of complex, unstructured and structured information, which does not lend ...

HDFS (Hadoop Distributed File System) – HDFS is the backbone of the Hadoop ecosystem that is responsible for storing large sets of structured, semi-structured and unstructured data. With HDFS, you can ...

That unstructured data creates problems for traditional databases; however, unstructured data is where Hadoop shines. An organization can collect all of these data streams and track how their ...

Unstructured data cannot always be handled in real time either. Clear rules should be defined around which data needs to be handled in which order. If the data is directly relevant to revenue then ...

Hadoop provides an economically viable storage layer without which the big data revolution would be impossible. The revolution will not be complete until we have practical techniques for turning this ...

Hadoop adoption is picking up as more unstructured data flows into the enterprise arena, but its rising importance will not relegate traditional relational database management systems (RDBMS)to ...

Hadoop may ultimately enable a renaissance in the user experience, but it hasn’t so far. After years of hype, you can’t blame business users who sometimes feel that Hadoop is a white elephant.

The distinction between structured and unstructured data is important because automated reasoning, one of the pillars of Web 40.0, requires both kinds of data analytics.

The specialist in collecting, monitoring and analyzing big data generated by machines is now extending its capabilities to the universe of unstructured text data with Hunk, a tool that works in ...