With the development of technology resources, organizations will increasingly depend on exploiting data for creating new products, services, innovation as well as changes in business processes. Big data is currently one of the most talked about issues in business and organizations. Big data is a collection of unstructured and multi-structured data that come from traditional and digital sources inside and outside companies representing sources for ongoing discovery and analysis.
Unstructured data refers to information that is not organized such as metadata, Twitter tweets, and other social media posts.
Multi-structured data refers to different types of organised data and data which can be generated from interactions between people and machines, for example, web applications, social networks and web log. Three significant characteristics of big data; high-volume, velocity, and variety; are important in obtaining, extracting, manipulating and interpreting it within an organization.
Many scholars believe that analysing, interpreting, and managing big data will help companies to understand their business environments, to respond to changes, and to create new products and services in order to keep their business fresh and new. Increasingly, long term commercial success is based on an ability to manage change and using data effectively. Many commentators stress the importance of leadership in the big data era. Leaders’ vision, their ability to communicate that vision, their creative thinking, their ability to spot a great opportunity, and the way that they support and deal with employees, customers, stockholders, and other stakeholders can surpass or mobilize change process. Moreover, effective leaders are able to bring together a group of competent professionals and data scientists to work with large quantities of data and information. Data scientists not only should possess statistical, analytical and creative IT skills but also they should be familiar with operations, processes and products within organizations. However, people with these competencies are difficult to find and in great demand.
Technologies such as the Hadoop framework, cloud computing and data visualization tools help skilled professionals to cope with the technical challenges. In fact, the increased volumes of data require major improvements in database technologies. Nowadays, open source platforms such as Hadoop have been designed to load, store and query massive data sets on a large, flexible grid servers, as well as perform advanced analytics. Analysing big data will not be valuable if professionals cannot understand and interpret the results of the analysis. Hence, organizations need great decision makers to examine all the assumptions made and retract the analysis to increase productivity and innovation at all organizational levels. Many scholars believe that automated administrative decision making can save time and improve efficiency. However, there is possibility of some error in computer systems that can lead to errors in interpretation of results. Hence, users should try to examine and verify the results produced by the computer.
By Mojgan Afshari
