Abstract
Data transformation from text files to database files, relational database management systems, and distributed database management systems in recent past has emerged a vast field of data warehouse. Currently data analytics is the most appealing field for the data scientists and challenges are very big as data volume is very huge. Not only data volume is high but the speed at which data is growing annually is exponentially. Data analytics has become a tool to grow the business by forecasting, business intelligence and decision support systems. In a simplified way, data is organized in the form of database, collective databases makes the data warehouse and the technologies like business intelligence, decision support system, and data analytics make use of data warehouse for their purpose. Big data is the enhanced form of the data warehouse which consists of the cloud storage and MapReduce-based architecture which consists of the clustering of data. This survey paper will give a high-level understanding of the existing data warehouse processing mechanisms including conventional processing and the distributed processing. Existing Extraction Transformation and Loading process will be analyzed for better understanding of the sub processes of the data warehouse building process.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abdelaziz E (2015) Optimisation of the queries execution plan in cloud data warehouses, pp 129–133
Anand N, Kumar M (2013) anand2013. In: Modeling and optimization of extraction- transformation-loading (ETL) processes in data warehouse: an overview
Bondarev A, Zakirov D (2016) Data warehouse on Hadoop platform for decision support systems in education
Chen Z, Zhao T (2012) A new tool for ETL process. In: Proceedings of the 2012 international conference on image analysis signal processing IASP 2012, pp 269–273
Hamad MM, Jihad AA (2011) An enhanced technique to clean data in the data warehouse. In: Proceedings of the 4th international conference on developments in eSystems engineering DeSE 2011, pp 306–311
Ishizuka Y, Chen W, Paik I (2016) Workflow transformation for real-time big data processing
Kabiri A, Chiadmi D (2012) A method for modelling and organazing ETL processes. In: 2nd international conference on innovative computing technology INTECH 2012, pp 138–143
Maji G, Sen S (2015) A data warehouse based analysis on CDR to depict market share of different mobile brands. In: 2015 annual IEEE India conference, pp 1–6
Mukkamala R (2016) Privacy-aware big data warehouse architecture
Parul, Nawab S, Teggihalli S (2015) Performance optimization for extraction, transformation, loading and reporting of data. In: Global conference on communication technologies GCCT 2015, no. Gcct, pp 516–519
Prema A, Pethalakshmi A (2013) Novel approach in ETL. In: Proceedings of the 2013 international conference on pattern recognition, informatics and mobile engineering PRIME 2013, pp 429–434
Sharma S, Kumar K (2016) ETLR—Effective DWH design paradigm. In: Proceedings of the international conference on data engineering and communication technology. Springer, pp 149–157
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sachin, S., Goyal, S.K., Avinash, S., Kamal, K. (2019). Nuts and Bolts of ETL in Data Warehouse. In: Rathore, V., Worring, M., Mishra, D., Joshi, A., Maheshwari, S. (eds) Emerging Trends in Expert Applications and Security. Advances in Intelligent Systems and Computing, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-2285-3_1
Download citation
DOI: https://doi.org/10.1007/978-981-13-2285-3_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2284-6
Online ISBN: 978-981-13-2285-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)