Harnessing the power of big data and Hadoop
Regardless of the industry, organizations across the globe have scrambled to deploy advanced analytics projects to improve their operational efficiency, reduce costs and increase revenue streams. According to Money Morning editor Tara Clarke, there were 2.7 zettabytes of data in existence as of 2012. By leveraging that information, organizations could improve various aspects of their operations according to their most immediate needs. Big data analytics have become so prevalent within the business community that failing to implement a sophisticated program could put a company at risk of falling behind the competition. For businesses that wish to reach their full potential and optimize performance and output, a big data analytics project has become a mission-critical utility.
Addressing big data challenges
However, some organizations have trouble properly launching such a complex operation. Getting the requisite databases, analytics tools and researchers in place can be difficult and, if poorly handled, can result in a lackluster project incapable of providing the level of insights promised at its inception. It's important that businesses choose an analytics solution that can address their various needs and provide superior processing capabilities. Apache Hadoop has long been the premier resource for creating sophisticated and effective analytics tools. The platform offers a number of benefits to prospective adopters, including the ability to house both structured and unstructured data. Traditional analytics software tools cannot extract any value from a data source as complex as streaming video, social media activity or audio recordings. The Hadoop architecture is made up of node clusters in which this information can be broken down and stored as usable information.
Hadoop can also help organizations break out of the analytics rut created by data silos. One of the major challenges businesses face with a new analytics project is supplying all available information with their big data tools. With proprietary software, compatibility issues can prohibit the use of certain data stores, reducing the accuracy and value of an analytics project. The Hadoop platform, however, is supported by a large community of open source developers who work to increase the number of applications with which Hadoop can interact. Furthermore, enterprise software providers and developers have formed partnerships to further expand Hadoop compatibility.
Some issues that arise when businesses launch an analytics program are not related to the technology itself but to the people operating it. A.T. Kearney partner and Bloomberg Businessweek contributor Laura Gurski explained that research teams at times have difficulty passing along information to their decision-making superiors and effectively conveying the value of their conclusions. Combating analysis paralysis requires an enterprise-wide commitment to the process. In order to receive the benefits of Hadoop-based big data projects, company leaders must first put their faith in the state-of-the-art technology.