This project analyses revenue data from Irish and Foreign owned Businesses. It compares and contrasts the informal data from Twitter(tweets) versus the formal data from the Department of Enterprise, Trade and Employment), Annual Business Survey of Economic Impact (ABSEI) 2019. This government dataset includes 15 different business sectors such as Food Drink & Tobacco, Chemicals, Computer, Electronic & Optical Products etc.
The dataset included annual sales, export, payroll, material and services for Irish owned and foreign Companies based in Ireland. There are 51 tables of data covering a timeline from 2000- 2019 in the dataset. The government data was processed in Excel /SPSS with a Progression Analysis to make Predictions. Stock trade market Twitter data (2019) was downloaded from Kaggle. Data was analysed using RStudio and text cloud. Sentiment analysis was performed using python to obtain patterns. Final conclusions were reached by contrasting government predictions results and patterns determined by twitter.
Mature student specialising in Data Analytics. Nine months experience in ETL on Informatica Power Center, TSFTP, DB, Client-Server, Services.
Nine years’ experience working with laser technology in Argentina. Highly numerate and a good knowledge of Excel, R and currently learning Python, Hadoop, MapReduce and SPSS.
Four years of leadership experience as swim coach while studying full time. Fluent in Spanish and English.
Expect to graduate in May 2022 and seeking to transition to a career in data analytics.