Responses to discussion

Running head: BUSINESS PROBLEMS ADDRESSED BY BIG DATA AND ROLE OF DATA WAREHOUSING 2

BUSINESS PROBLEMS ADDRESSED BY BIG DATA AND ROLE OF DATA WAREHOUSING 2

Business Problems Addressed by Big Data Analytics and Role of Data Warehousing

Santosh Shrestha

University of Cumberlands

Business Intelligence - ITS-531

Dr. Steve Hallman

July 29, 2020

Business Problems Addressed by Big Data Analytics and Role of Data Warehousing

The top business problem addressed by Big Data analytics are cost reduction and process efficiency with enhanced customer experience. Process efficiency and cost reduction, Brand management, Revenue maximization, cross-selling, and up-selling, Enhanced customer experience, Churn identification, customer recruiting, Improved customer service, Identifying new products and market opportunities, Risk management, Regulatory compliance, and Enhanced security capabilities are some of the problems that can be addressed using Big Data analytics (Sharda et al., 2020, p. 521-522). Big Data Analytics with the right tools and expertise can make use of vast data available to bring these values to the businesses to bring competitive advantages.

With the rise of Big Data in recent years, questions are arising whether the existing data warehousing is on the verge of being obliterated by this new technology. The reason behind the emergence of Big data is the emergence of the variety and complexity of data. Big Data can work with these unstructured data, which brings various advantages over data warehousing. However, data warehousing has been efficiently serving as a decision support system for a decade and can work with structured data. The direction of the industry over the next few years will likely be moving toward more tightly coupled Hadoop and relational DBMS-based data warehouse technologies, both software and hardware (Sharda et al., 2020, p. 532). Instead of replacing the data warehousing, there is the scope if integrating it with Big Data to get the most out of it. There are many benefits of such integrations, including eliminating the need to install and maintain multiple systems, reducing data movement, providing a single metadata store for application development, and providing a single interface for both business users and analytical tools (Sharda et al., 2020, p. 532). Big Data Analysis is the vast new data science realm that is being explored in recent years because of the abundance of unstructured data coming from IoT, streaming media as such. It is essential that the existing data warehousing containing vast business data has to be incorporated together to make the most use of this technological evolution.

Reference

Sharda, R., Delen, D., Turban, E. (2020). Big Data. Analytics, data science, & artificial

intelligence: Systems for decision support (pp. 521-532). NJ, Pearson.