DATA WRANGLING AND R

BUS5DWR

2020

Credit points: 15

Subject outline

This subject introduces you to the various techniques of data wrangling with a strong focus on hands-on experience in R and Structured Query Language (SQL) programming. It will cover the basic concepts in relational database design including Entity Relationship (ER) modelling and SQL as a tool for basic data wrangling. You will also learn various types of data sources and common data formats. The subject teaches you R programming language for you to perform data wrangling tasks, including data import and export, basic data integration and data assessment. Upon completion, you will be able to perform a variety of data wrangling tasks using SQL and R for different kinds of data types.

School: La Trobe Business School (Pre 2022)

Credit points: 15

Subject Co-ordinator: Binh Tran

Available to Study Abroad/Exchange Students: No

Subject year level: Year Level 5 - Masters

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: Enrolled in LMBAN or LCBAN or LGBAN

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Quota Management Strategy: Merit based quota management

Quota-conditions or rules: By the order of application to subject coordinator.

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Learning resources

The Essentials of Data Science

Resource Type: Book

Resource Requirement: Recommended

Author: Williams, G.

Year: 2017

Edition/Volume: N/A

Publisher: CRC Press

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Microsoft SQL Server 2016: A Beginner's Guide

Resource Type: Book

Resource Requirement: Recommended

Author: Petkovic, D.

Year: 2016

Edition/Volume: N/A

Publisher: McGraw-Hill Education

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Data Wrangling with R (Use R!)

Resource Type: Book

Resource Requirement: Recommended

Author: Boehmke, B.

Year: 2016

Edition/Volume: N/A

Publisher: Springer International Publishing

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

COMMUNICATION - Communicating and Influencing
DISCIPLINE KNOWLEDGE AND SKILLS
INQUIRY AND ANALYSIS - Critical Thinking and Problem Solving

Intended Learning Outcomes

01. Design good structured database for data wrangling.
02. Compare and contrast various data formats and motivations for data wrangling.
03. Construct SQL and R code to wrangle data.
04. Formulate data needs and propose data wrangling questions for a new problem.

City Campus, 2020, Semester 1, Night

Overview

Online enrolment: Yes

Maximum enrolment size: 120

Subject Instance Co-ordinator: Binh Tran

Class requirements

Lecture/WorkshopWeek: 10 - 22
One 3.00 hours lecture/workshop per week on weekdays at night from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

Individual Assignment (2000 words), SQL designDemonstrate knowledge in database design and proficiency in data wrangling using SQL.

N/AN/AN/ANo40SILO1

Individual Assignment (1000 words), Report on recent data wrangling topicDemonstrate knowledge on various data sources, data format and motivation for data wrangling and its implications to business analytics.

N/AN/AN/ANo20SILO2

Individual Assignment (2000 words), R and SQL codingDemonstrate proficiency in data wrangling using R and SQL.

N/AN/AN/ANo40SILO3, SILO4

City Campus, 2020, Semester 2, Night

Overview

Online enrolment: Yes

Maximum enrolment size: 120

Subject Instance Co-ordinator: Binh Tran

Class requirements

Lecture/WorkshopWeek: 31 - 43
One 3.00 hours lecture/workshop per week on weekdays at night from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

Individual Assignment (2000 words), SQL designDemonstrate knowledge in database design and proficiency in data wrangling using SQL.

N/AN/AN/ANo40SILO1

Individual Assignment (1000 words), Report on recent data wrangling topicDemonstrate knowledge on various data sources, data format and motivation for data wrangling and its implications to business analytics.

N/AN/AN/ANo20SILO2

Individual Assignment (2000 words), R and SQL codingDemonstrate proficiency in data wrangling using R and SQL.

N/AN/AN/ANo40SILO3, SILO4