LibGuides: Data Analytics Subject Guide: Library Resources

This guide will give you an introduction to finding information on data analytics. You can use it to:

locate books, eBooks and journal articles
search relevant databases
connect to useful websites
reference properly and avoid plagiarism

Check Out These Books

Data Mining: Practical Machine Learning Tools and Techniques by Ian H. Witten; Eibe Frank; Mark A. Hall; Christopher J. Palestro
2016, 4th edition. Shelfmark: 006.3
Statistics by James McClave; Terry Sincich
2014, 12th edition. Shelfmark: 519.5
Building the Data Warehouse by William H. Inmon
2005, 4th edition. Shelfmark: 005.74

The books in the library are organised first by number and then alphabetically by author's surname. Each book number corresponds to a subject area. Use the Library Catalogue to search for books from your reading lists and course material. If you need help using the Library Catalogue, take a look at our Finding Books guide.

Remember to consult your reading lists and course material for more detail on your recommended texts. To help you get started the numbers below may be helpful for finding books. You can take a look at the Library Map to see where the subject areas are located in the library

Data Analytics Subject Areas:

005.74	Database Systems
006.3 / 006.312	Data Mining
519.5	Statistics for Business and Economics/Data Analysis
658	Management
658.05	Computer Applications
658.4038	Business Information Systems / Management Information Systems
808.066 / 808.0666	Academic Writing / Research in Computing

You can also access some relevant material by using the eBooks available through the library. You can access our main ebook databases here.

Recommended Data Analytics eBooks:

	Barker, T. (2013) Pro data visualization using R and JavaScript. O'Reilly.		Linoff, G. S. and Berry, M. J. A. (2011) Data mining techniques: For marketing, sales, and customer relationship management. 3rd edn. O'Reilly.
	Connolly, T. M. and Begg, C. E. (2015) Databases systems: A practical approach to design, implementation and management. 6th edn. VLeBooks.		McClave, J. and Sincich, T. (2017) Statistics. 13th edn. VLeBooks.
	EMC Education Services (2012) Information storage and management: Storing, managing, and protecting digital information in classic, virtualized, and cloud environments. 2nd edn. O'Reilly.		McKinney, W. (2017) Python for data analysis. 2nd edn. O'Reilly.
	Holmes, A. (2014) Hadoop in practice. 2nd edn. O'Reilly.		Russell, M. A. and Klassen, M. (2019) Mining the social web. 3rd edn. O'Reilly.
	James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013) An introduction to statistical learning: With applications in R. VLeBooks.		Salkind, N. J. and Frey, B. (2020) Statistics for people who (think they) hate statistics. 7th edn. SAGE Research Methods.
	Kelleher, J. D., D'Arcy, A., and Mac Namee, B. (2015) Fundamentals of machine learning for predictive data analytics: Algorithms, worked examples, and case studies. ProQuest eBook Central.		Teetor, P. and Long, J. D. (2019) R Cookbook. 2nd edn. O'Reilly.
	Kimball, R. and Ross, M. (2013) The data warehouse toolkit: The definitive guide to dimensional modeling. 3rd edn. O'Reilly.		Ware, C. (2012) Information visualization. 3rd edn. O'Reilly.
	Kirk, A. (2019) Data visualisation: A handbook for data driven design. 2nd edn. SAGE Research Methods.		White, T. (2015) Hadoop: The definitive guide. 4th edn. O'Reilly.
	Lantz, B. (2015) Machine learning with R. 2nd edn. O'Reilly.		Witten, I. H., Frank, E., Hall, M. A. and Pal, C. J. (2016) Data mining: Practical machine learning tools and techniques. 4th edn. O'Reilly.
	Laudon, K. C. and Laudon, J. P. (2018) Management information systems: Managing the digital firm. 15th edn. VLeBooks.		Zobel, J. (2014) Writing for computer science. 3rd edn. VLeBooks.

You can find more eBooks by searching the library catalogue or check out our eBooks page and our eBooks guide for further details.

In order to access journal articles and other online material for your subject area, you can consult the recommended databases that are relevant to your particular subject area individually and are displayed below. For a full list of databases NCI Library subscribes to, go to A-Z Databases on the library webpage.

Recommended Data Analytics Databases:

Database & Subject Areas		Access Through
ACM Digital Library Subject Areas: Computing		Discovery A-Z Databases User Guide
Business Source Ultimate Subject Areas: Accounting, Business, Economics, Finance, Human Resources, Law, Management, Marketing, Psychology		Discovery A-Z Databases User Guide
IEEE Xplore Subject Areas: Computing		Discovery A-Z Databases User Guide
Lecture Notes in Computer Science Subject Areas: Computing		Discovery A-Z Databases User Guide
ProQuest Business Premium Collection Subject Areas: Business, Entrepreneurship & Management		Discovery A-Z Databases User Guide
SAGE Journals Subject Areas: Economics, Management & Marketing		Discovery A-Z Databases User Guide
SAGE Research Methods Over 800 books, reference works, journal articles and videos from SAGE’s research methods list. Subject Areas: writing a research question, conducting a literature review, choosing a research method, collecting and analysing data and writing up findings		A-Z Databases User Guide
ScienceDirect Offers journal articles and book chapters from 2,500 journals and nearly 20,000 books. Subject Areas: Computing		Discovery A-Z Databases User Guide
Scopus Abstract & citation database of peer-reviewed literature review Subject Areas: Science, Technology, Medicine, Social Sciences, Arts & Humanities		Discovery A-Z Databases User Guide
Statista Statistics platform, over 1.5 million data sets Subject Areas: Business, Commerce, Company Profiles, Finance, Marketing, Statistics, Reports		For off campus access go here User Guide

You can access the journals below through the A-Z eJournals page or through Discovery.

Recommended Data Analytics Journals:

ACM Transactions on Knowledge Discovery from Data (Database: ACM Digital Library)

Communications of the ACM (Database: ACM Digital Library / Business Source Ultimate)

Data Mining & Knowledge Discovery (Database: ProQuest Business Premium Collection)

IEEE Transactions on Knowledge & Data Engineering (Database: IEEE Xplore)

Information Visualization (Database: SAGE Journals)

In addition to using the college resources, your reading lists also recommend consulting a number of external sites. Below is a selection of some recommended websites.

Recommended Data Analytics External Websites:

Apache Cassandra	http://cassandra.apache.org/
Apache Hadoop	http://hadoop.apache.org/
Apache HBase	http://hbase.apache.org/
Central Statistics Office	https://www.cso.ie/en/index.html
Cloudera - The Hadoop Ecosystem	https://www.cloudera.com/developers/cloudera-labs.html
Dataset Search	https://datasetsearch.research.google.com/
David Lane	http://davidmlane.com/hyperstat/
InfoVis: Wiki	https://infovis-wiki.net/wiki/Main_Page
Interaction Design Foundation - Data Visualization for Human Perception	https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception
Lescovec, J., Rajaraman, A., Ullman, J. - Mining of Massive Datasets	http://www.mmds.org/
MIT Open Courseware - Introduction to Algorithms	https://ocw.mit.edu/courses/6-006-introduction-to-algorithms-spring-2020/
MongoDB	https://www.mongodb.com/
MySQL	https://www.mysql.com/
R Project	http://www.r-project.org/

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Keith Brittle	Shannon Mallon