Published May 28, 2020 | Version Version 1
Journal article Open

DATA ANALYSIS AND ETL TOOLS IN BUSINESS INTELLIGENCE

Creators

  • 1. Computer Science Engineering Dept SVKM'S Shri Bhagubhai Mafatlal Polytechnic Mumbai, India

Contributors

  • 1. AM Publications

Description

Business intelligence (BI) is a collection of software and services to convert facts into actionable observations. These observations can impact strategic and tactical business decisions of an enterprise. BI can provide users with exhaustive intelligence about the state of the business with the assistance of tools which can access and scrutinize data sets and deliver pinpointing findings in reports and summaries etc. The technology has considerably advanced in the area of information systems through the evolvement of DSS (Decision Support Systems) to EIS (Executive Information Systems) to Business Intelligence systems. ETL (Extract, Transform, and Load) is a procedure of pulling out data from various data sources and processing them according to business calculations and transferring the reformed data into a data warehouse. ETL function lies at the core of Business Intelligence systems because of the in-depth analytics data it provides. Enterprises can gain past, current, and projecting views of real business data with ETL.

Notes

Business intelligence and data warehousing have different objectives. BI is primarily dedicated for producing operational or strategic business insights like product positioning and product pricing, profitability, sales performance, forecasting, strategic directions on a broader level, while a data warehouse has its significance in storing all the company's data from heterogeneous sources in a single place. BI systems utilize data warehouse while data warehouse acts as a foundation for business intelligence.

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Related works

Cites
Journal article: http://www.irjcs.com/volumes/Vol7/iss-5/07.MYCS10094.pdf (URL)
Is cited by
Journal article: 10.26562/irjcs.2020.v0705.007 (DOI)

References

  • 1. Paulraj Ponniah, "DATA WAREHOUSING FUNDAMENTALS A Comprehensive Guide for IT Professionals" A Wiley-Interscience Publication New York, 2001.
  • 2. Panos Vassiliadis, "A Survey of Extract–Transform–Load Technology", International Journal of Data Warehousing & Mining, 5(3), 1-27, July-September 2009.
  • 3. Sonali Vyas and Pragya Vaishnav, "A comparative study of various ETL process and their testing techniques in data warehouse", Journal of Statistics and Management Systems, 20:4, 753-763, 2017.
  • 4. Mohammad Atwah Al-ma'aitah. "The Role of Business Intelligence Tools in Decision Making Process", International Journal of Computer Applications 73(13):24-32, July 2013.
  • 5. Nitin Anand, "Application of ETL Tools in Business Intelligence", International Journal of Scientific and Research Publications, Volume 2, Issue 11, November 2012, ISSN 2250-3153.
  • 6. Ranjith Katragadda, Sreenivas Sremath Tirumala and David Nandigam, "ETL tools for Data Warehousing: An empirical study of Open Source Talend Studio versus Microsoft SSIS", WCCAIS 2015.
  • 7. M. M. Al-Debei, "Data Warehouse as a Backbone for Business Intelligence: Issues and Challenges," European Journal of Economics, Finance and Administrative Sciences, vol.33, 2011.
  • 8. Vassiliadis, Panos, "A Survey of Extract-Transform-Load Technology". International Journal of Data Warehousing and Mining. 5. 1-27, 2009.
  • 9. Ranjan, J."Business Intelligence: Concepts, Components, Techniques and Benefits", Journal of Theoretical and Applied Information Technology, Vol 9. No 1, pp 060 - 070 ,2009
  • 10. Microsoft, "Ssis technical report," Microsoft, SSIS. Retrieved from microsoft.com, Tech. Rep., [Online]. Available: https://docs.microsoft.com/en-us/sql/integration-services/sql-server-integration-services

Subjects

Computer Science & Engineering
http://www.irjcs.com/volumes/Vol7/iss-5/07.MYCS10094.pdf