Hadoop is an open source framework for managing vast amounts of distributed data (big data) that works in conjunction with MapReduce, a framework to support distributed computing for large data sets on hardware clusters.
The combination of BIRT’s open source, flexible approach to business intelligence and Hadoop’s data scalability enables organizations to build information applications that give the full range of end users — including business analysts and non-technical users — valuable insight into data stored in Hadoop, Acutuate said.
"It is clear that there is a need in the market for analysis and exploration of large-scale data. Increasingly, organizations that manage large amounts of structured relational data also need to process large amounts of semi-structured data such as the type found in web logs and application logs," said David Menninger, vice president and research director at Ventana Research.
Vendors small and large, among them IBM, have been tapping into Hadoop to address big data challenges, such as analyzing large amounts of unstructured and social media data.
Actuate said application developers are now able to use BIRT 3.7 from the Eclipse Foundation to access Hadoop using Hive Query Language (HQL).
BIRT 3.7 provides native access to Hadoop as a data source for analysis, dashboards, reporting and custom business intelligence (BI) and information applications, and it can be used to build data sets or data visualizations that seamlessly combine Hadoop data with other data sources, including SQL databases, XML data, document archives and flat files.
Because of the open standards that BIRT adheres to, it is able to leverage pre-built MapReduce functions and rules, enabling developers to quickly get started on building applications to explore their Hadoop data.
Actuate said Hadoop readily accommodates change because it stores raw data in any format, and therefore does not require complex data and schema mappings that are time-consuming to set up and difficult to maintain.
In turn, BIRT enables developers to build BI applications on top of Hadoop that are equally flexible yet allow organizations to use Hadoop for decision support, monitoring, batch reporting and analysis.