A Conceptual Study on Big Data Applications for Business Integration; a Techno-Business Leadership Perspective

Big data analytics is a trending practice that many companies are adopting. The analytics process includes the deployment and use of big data analytics tools, that improves operational efficiency, drive new revenue and gain competitive advantages over business rivals. The descriptive analytics focuses on describing something that has already happened, as well as suggesting its root causes. Descriptive analytics, which remains the lion's share of the analysis performed, typically hinges on basic querying, reporting and visualization of historical data. Alternatively, more complex predictive and prescriptive modeling can help companies anticipate business opportunities and make decisions that affect profits in areas such as targeting marketing campaigns, reducing customer churn and avoiding equipment failures. With predictive analytics, historical data sets are mined for patterns indicative of future situations and behaviors, while prescriptive analytics subsumes the results of predictive analytics to suggest actions that will best take advantage of the predicted scenarios.