AUTOMATED DATA GATHERING FOR DESTINATION DRIVEN ‘RENEWABLES AND EFFICIENCY INCENTIVES PROGRAMS’ DATA WAREHOUSE USING LINEAR REGRESSION
Author’s Name : K R Nishanth | Dr S Karthik
Volume 05 Issue 02 Year 2018 ISSN No: 2349-3828 Page no: 11-13
Abstract:
In this proposed method the data warehousing schedule is automatically calculated with the help of a machine learning algorithm called ‘linear regression’ and will be used to predict when to request for new data from operational data sources. In this proposed system the frequency and the time of the data being delivered to the data warehouse are initially recorded for a particular period of time and is trained with linear regression algorithm. With the trained model, the time for the data delivery can be predicted and a request is made to the ‘Renewables and efficiency incentives programs’ database. According to this prediction, the data can be requested at the time and be stored in the data warehouse. The stored information can further be used for other purposes like data mining and analytics.
Keywords:
Data Warehouse; Machine Learning; Linear Regression; Scheduling
References:
- Silberschatz A, Korth H F, Sudarshan S, (1997) “Database System Concepts”, McGraw-Hill Series in Computer Science
- B. Ganapathy Subramaniam, T Rama Prabha (2017),”Linear Regression in Machine Learning”, Rungta International Journal of Computer Science and Information Technology, Vol 2 Issue 1 & 2
- Vishal Gour et. al. (IJCSE) “Improve Performance of Extract, Transform and Load (ETL) in Data Warehouse”, International Journal on Computer Science and Engineering Vol. 02, No. 03, 2010, 786-789
- J.Anitha et al, “ETL Work Flow for Extract Transform Loading”, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.6, June- 2014, pg. 610-617