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='''Introduction to Analytics Practicum''' =
 
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[[Image:logo.png]]
 
 
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[[Main_Page| <font color="#FFFFFF">About</font>]]
  
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The [[Analytics]] Practicum module (ANLY482) is a compulsory module for those who are taking the [[Analytics]] [http://sis.smu.edu.sg/2nd-majors-analytics Second Major program]. It involves a project that assess the students' ability to apply analytics in real-time events extensively. These projects come from both the academics and industry. Students can also get a good sense of how [[analytics]] are used in their field of study.
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[[ANLY482_AY2017-18_Term_2| <font color="#FFFFFF">Current Practicums</font>]]
  
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Students are encouraged to observe statistical fundamentals and maintain good analytical minds that give a good, careful and thoughtful study of the data. Other than having a [[positivist]] mindset, students are also encouraged to cultivate an [[interpretivist]] mindset, where any form of interpretation is never definitive and a search of truth is strongly evident, regardless of how treacherous the search may be.
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[[ANLY482_Past_Practicums: Past Practicums| <font color="#FFFFFF">Past Practicums</font>]]
  
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The field of data analytics is a science field but students should also have a good blend of the arts and science of studying data. It is not enough to conclude scientifically; one should also paint a story that invokes the background, essence and meaning of the scientific results. That requires the art of studying data.
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[[ANLY482_Grading: Current Practicums | <font color="#FFFFFF">Grading & Deliverables</font>]]
  
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[[Code_of_Ethics|Ethics]] play a big role in data analytics. Data should not be fabricated; results should not be inflated or artificial. Observing proper ethics with a good conscience will ensure a bright future for those who undertake the role of a data analyst.
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[[ANLY482_FAQ: FAQ | <font color="#FFFFFF">Downloads & FAQ</font>]]
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'''Welcome to the [[Analytics]] Practicum (ANLY482)! - a place where students turn into professional analysts.'''
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'''<font size = 5>Welcome to ANLY482 Analytics Practicum</font>
  
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=2014/2015 Term 1=
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<div style="background: #fdf5e6; padding: 13px; font-weight: bold; text-align: left; line-height: wrap_content; text-indent: 20px;font-size:20px; font-family:helvetica"><font color= #3d3d3d>Overview</font></div>
  
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In recent years, there is an increasing use of data analytics to discover business issues and to drive business strategy throughout organizations. This has created a parallel rising demand for business graduates, who understand how to use data analytics, to solve business issues. To prepare students taking Analytics Second Major to cope with this demand, this course provides students the practical experience on how to apply the analytics techniques and tools that they have learned in class to help companies solve real world challenges.
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<tr>
 
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<th>Supervisor</th>
 
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<th width=10%>Team</th>
 
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<th>Project</th>
 
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<th width=200>Member(s)</th>
 
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<th>Sponsor</th>
 
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<td>[http://sis.smu.edu.sg/faculty/profile/83109/Seema%20CHOKSHI Seema Chokshi]</td>
 
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<td>[[Kolaveri Di Social Analytics Project]]</td>
 
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<td>"[http://www.youtube.com/watch?v=YR12Z8f1Dh8|Why This Kolaveri Di]" is a Tamil song from the soundtrack of Tamil film 3. It was written and sung by actor [http://en.wikipedia.org/wiki/Dhanush Dhanush] and composed by music director [http://en.wikipedia.org/wiki/Anirudh_Ravichander Anirudh Ravichander]. The song was officially released on 16 November 2011, and it instantly became viral on social networking sites for its quirky "[http://en.wikipedia.org/wiki/Tanglish Tanglish]" lyrics. Soon, the song became the most searched YouTube video in India and an internet phenomenon across Asia. Within a few weeks, YouTube honoured the video with a Recently [http://www.sify.com/movies/kolaveri-bags-youtube-gold-award-news-news-lmhmfCidgif.html?scategory=tamil Most Popular Gold Medal Award] for receiving a large number of hits in a short time. The objective of this project is to identify the key element(s) that explains the success of this video, particularly for its capability in drawing listeners and spreading its viral effect over the online domain. The analysts are required to submit a report, detailing out these elements along with some recommendations that could help to replicate its success.
 
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</td>
 
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#[[Lee Jaehyun]]
 
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#[[Chan Wei Yin]]</td>
 
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<td>[http://www.smu.edu.sg/faculty/profile/9528/Srinivas%20K%20REDDY Srinivas K Reddy]</td>
 
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<td>[http://sis.smu.edu.sg/faculty/profile/83109/Seema%20CHOKSHI Seema Chokshi]
 
  
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'''IMPORTANT:''' ANLY482 Analytics Practicum is a compulsory module for students who are taking the [http://sis.smu.edu.sg/2nd-majors-analytics Analytics Second Major program].
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<td>[[Visualization of Consumer Satisfaction]]</td>
 
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<td>Consumer research has been a hot topic. Businesses and government agencies are interested to know the satisfaction levels of Singaporean consumers and effectively take actions that can create valuable and meaningful impact in the society. This project explores these satisfaction levels. It uses the respondent level data from the [http://ises.smu.edu.sg/sites/default/files/ises/pdf/csisg2013_q1_executivesummary.pdf|Customer Satisfaction Index of Singapore (2008-2013)]. The objective of this project is to produce a dashboard that shows trends of consumer satisfaction visually.</td>
 
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<td>
 
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#[[Mohamed Yousof Bin Shamsul Hameed]]
 
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#[[Kee Eng Sen]]</td>
 
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<td>[http://www.smu.edu.sg/faculty/profile/9505/Marcus%20LEE Marcus Lee]</td>
 
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<td>[http://sis.smu.edu.sg/faculty/profile/83109/Seema%20CHOKSHI Seema Chokshi]</td>
 
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<td>[[Twitter Analytics:Home|Twitter Analytics]]</td>
 
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<td>The background of the project is horizon scanning; creating an analytical platform that is scanning the online (social/established data) to identify upcoming topics and keywords clusters. The objective is to not stop at the cloud creation but to be able to provide a time series analysis and forecast of the ‘relevance’ of the topic over the course of X number of days</td>
 
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<td>
 
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#[[Fransisca Fortunata]]</td>
 
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<td>[http://sis.smu.edu.sg/master-it-business/faculty-and-staff/adjunct-faculty/hardoon David Hardoon]</td>
 
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</tr>
 
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</table>
 
  
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= Grading =
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<div style="background: #fdf5e6; padding: 13px; font-weight: bold; text-align: left; line-height: wrap_content; text-indent: 20px;font-size:20px; font-family:helvetica"><font color= #3d3d3d> Prerequisites</font></div>
  
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===Project Proposal===
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<b>Analytics Foundation</b> is a Pre-Requisite.  It is recommended to take the Practicum course after completing 2 to 3 other analytics electives in order to make the most of the Practicum course. Each listed Analytics Practicum project, might have a list of additional recommended courses which are closely associated with the project area and will come in handy if you take up that project.
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[[Update of Wikipage]]: 1%<p>
 
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[[Proposal Report]]: 14%
 
  
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===Mid-Term Presentation and Report===
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<div style="background: #fdf5e6; padding: 13px; font-weight: bold; text-align: left; line-height: wrap_content; text-indent: 20px;font-size:20px; font-family:helvetica"><font color= #3d3d3d>Scope of the Practicum</font></div>
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[[Mid-Term Presentation]]: 10%</p><p>
 
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[[Mid-Term Report]]: 15%</p><p>
 
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[[Mid-Term Update of Wikipage]]: 5%</p><p>
 
  
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===Final Presentation and Report===
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Students taking this course are required to form a team of three members.  They will work closely with their industry sponsor to identify the business problem, to compile the necessary data, to transform the data into analytics data mart, to perform the analysis by using appropriate analytics techniques and tool(s) and to present their findings to the stake-holder of the project sponsor organisation.  Last but not least, the students are required to document the lesson learned through working on the project in the form of practice research paper and present their paper in the Undergraduate Conference of Data Analytics.
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[[Final Report]]: 25%</p><p>
 
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[[Final Presentation]]: 15%</p><p>
 
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[[Project Poster]]: 10%</p><p>
 
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[[Final_Update_of_Wikipage|Update of Wikipage]]: 5%
 
  
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= Administrator =
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For more information please read the [http://sisapps.smu.edu.sg/CDDR/Courses.aspx?P=104&C=1426&CT=(ANLY482)%20Analytics%20Practicum Course Design Document]<br/>
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The administrator for this wikipage is [http://sis.smu.edu.sg/about/staff/instructors/daniel-koh-kian-wei Daniel]. You may contact him at danielkoh@smu.edu.sg .
 

Latest revision as of 16:50, 12 March 2018

About

Current Practicums

Past Practicums

Grading & Deliverables

Downloads & FAQ

 

Welcome to ANLY482 Analytics Practicum

Overview

In recent years, there is an increasing use of data analytics to discover business issues and to drive business strategy throughout organizations. This has created a parallel rising demand for business graduates, who understand how to use data analytics, to solve business issues. To prepare students taking Analytics Second Major to cope with this demand, this course provides students the practical experience on how to apply the analytics techniques and tools that they have learned in class to help companies solve real world challenges.

IMPORTANT: ANLY482 Analytics Practicum is a compulsory module for students who are taking the Analytics Second Major program.

Prerequisites

Analytics Foundation is a Pre-Requisite. It is recommended to take the Practicum course after completing 2 to 3 other analytics electives in order to make the most of the Practicum course. Each listed Analytics Practicum project, might have a list of additional recommended courses which are closely associated with the project area and will come in handy if you take up that project.

Scope of the Practicum

Students taking this course are required to form a team of three members. They will work closely with their industry sponsor to identify the business problem, to compile the necessary data, to transform the data into analytics data mart, to perform the analysis by using appropriate analytics techniques and tool(s) and to present their findings to the stake-holder of the project sponsor organisation. Last but not least, the students are required to document the lesson learned through working on the project in the form of practice research paper and present their paper in the Undergraduate Conference of Data Analytics.

For more information please read the Course Design Document

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