Next Generation Data Warehousing for Destination Marketing With Big Data Technologies

View Sample PDF

Author(s): Aye Thiri Nyunt (Marwadi University, India), Brij Kotak (Marwadi University, India), Ravi Chauhan (Marwadi University, India), Rituraj Jain (Marwadi Uinversity, India), Kumar J. Parmar (Marwadi University, India), Damodharan Palaniappan (Marwadi University, India)and T. Premavathi (Marwadi University, India)
Copyright: 2026
Pages: 38
Source title: Maximizing Destination Marketing Strategies in the Digital Era
Source Author(s)/Editor(s): Mohammad Soliman (Sultan Qaboos University, Oman)and Islam Elgammal (Suez Canal University, Egypt)
DOI: 10.4018/979-8-3693-9939-2.ch006

Keywords: Business & Management / Business Science Reference / Hospitality, Travel & Tourism Management / Marketing and Consumer Behavior

Purchase

View Next Generation Data Warehousing for Destination Marketing With Big Data Technologies on the publisher's website for pricing and purchasing information.

Abstract

This chapter will discuss evolution of traditional legacy data warehousing into modern big data technology for efficiently managing and analyzing data. Data warehousing brings together structured data from diverse sources on a business. Traditional systems have changed from batch processing to cloud computing and machine learning when handling large unstructured data and real-time information. Big data tools such as Hadoop and Apache Spark make traditional data warehousing faster. Cloud-based data management solutions, such as Amazon Redshift and Google BigQuery, scale and manage cost-effectively. This hybrid approach allows organizations to gain insights, adapt to market directions, and stay competitive in digital transformation.

The IRMA Community

Research IRM

Next Generation Data Warehousing for Destination Marketing With Big Data Technologies

Purchase

Abstract

Related Content

IRMA Sponsors