辅导案例-FIT5141-Assignment 3

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FIT 5141, 2019 – Advanced Topics in
Information Technology
Assignment 3 useful resources: R Libraries

This document provides additional resources for FIT5141 Assignment 3.


1. Security Aspects of MongoDB

The first two items are sufficient to help students protect their MongoDB applications:
• General Security aspects of MongoDB (Authentication, Authorization, TLS/SSL):
https://docs.mongodb.com/manual/security/
• Security Checklist (10 security considerations in MongoDB):
https://docs.mongodb.com/manual/administration/security-checklist/
Extra resources
• MONGODB SECURITY HUB - Best practices on securing your MongoDB database:
https://resources.mongodb.com/mongodb-security?jmp=hero&_ga=2.221452632.179190120.1500701507-
1505179281.1500115196
• How to Avoid a Malicious Attack That Ransoms Your Data:
https://www.mongodb.com/blog/post/how-to-avoid-a-malicious-attack-that-ransoms-your-data
and
https://www.mongodb.com/blog/post/how-to-avoid-a-malicious-attack-that-ransoms-your-data#suggested-
steps
• How to secure MongoDB – because it isn't by default and thousands of DBs are being hacked:
https://www.theregister.co.uk/2017/01/11/mongodb_ransomware_followup/
• Mongodb - Security Weaknesses in a typical NoSQL database:
https://www.trustwave.com/Resources/SpiderLabs-Blog/Mongodb---Security-Weaknesses-in-a-typical-
NoSQL-database/
• How To Securely Configure a Production MongoDB Server:
https://www.digitalocean.com/community/tutorials/how-to-securely-configure-a-production-mongodb-server
• The essential guide to MongoDB security:
http://www.infoworld.com/article/3164504/security/the-essential-guide-to-mongodb-security.html
• How to secure MongoDB with username and password:
https://stackoverflow.com/questions/4881208/how-to-secure-mongodb-with-username-and-password
• Get Serious About Data Protection to Secure MongoDB:
https://securityintelligence.com/get-serious-about-data-protection-to-secure-mongodb/
• How to secure MongoDB:
https://codewithintent.com/how-to-secure-mongodb/
and
https://www.youtube.com/watch?v=Jsb-9iM_tiw

2. Tableau Integration with R
1) in "R", the "Rserve" package should be installed and run:
• install.packages("Rserve")
• library(Rserve)
• Rserve()

2) in "Tableau" Desktop, go to the "Help > Settings and Performance > Manage External Service
Connection..." and test the validity of the R connection.
*NOTE: prior to Tableau 10.1, the name of the "Manage External Service Connection..." was "Manage R
Connection...". They generalized it to support for "Python" services as well. :-)
2

After connecting to R, we can use a set of four functions to pass R expressions to external services and
obtain a result:
-SCRIPT_BOOL
-SCRIPT_INT
-SCRIPT_REAL
-SCRIPT_STR

Now, the following resources can be of help:
• Using R within Tableau (I could not open the link because currently, I do not have Tableau
account, but I am sending this in case you have one): https://www.tableau.com/learn/tutorials/on-
demand/using-r-within-tableau
• Using R and Tableau: https://www.tableau.com/sites/default/files/media/using-r-and-tableau-
software_0.pdf
• Quick Start Guide for Using R with Tableau: this PDF file
• Tableau 8.1 and R: https://www.tableau.com/about/blog/2013/10/tableau-81-and-r-25327
• Passing expressions to external services in
Tableau: https://onlinehelp.tableau.com/current/pro/desktop/en-us/r_connection_manage.html
• Getting started with Tableau8.1 & R: http://www.jenunderwood.com/2013/10/05/getting-started-
with-tableau-8-1-beta-r-part-1
• Integrating Tableau and R for data analytics in four simple
steps: http://www.simafore.com/blog/bid/120209/Integrating-Tableau-and-R-for-data-analytics-in-
four-simple-steps
• Dream Team - Combining Tableau and R: https://www.r-bloggers.com/dream-team-combining-
tableau-and-r/
• Tableau's R Integration: http://www.associationanalytics.com/2017/01/31/tableaus-r-integration/
• Tableau and R Integration: https://community.tableau.com/docs/DOC-5313

Examples:
• Logistic Regression in Tableau using R: https://boraberan.wordpress.com/2013/12/16/logistic-
regression-in-tableau-using-r/
• other factors/configs and examples: https://boraberan.wordpress.com/
• Tableau with R - Clustering: http://www.jenunderwood.com/2014/01/19/tableau-with-r-part-2-
clustering/
• Predict Customer Churn Using R and Tableau: https://dzone.com/articles/predict-customer-churn-
using-r-and-tableau

--------------------------------------

Also, these are some simple video resources in explaining the process of R-Tableau integration and
one sample predictive analytics with R example in Tableau:
• Tableau&R - Establish a connection:
https://www.youtube.com/watch?v=LsKQHTAJJWk
• Tableau&R Overview:
https://www.youtube.com/watch?v=UAkC_Z6Ebqc
• Tableau 8.1 - Predictive Analytics with R:
https://www.youtube.com/watch?v=Y7OJjIeKcBM
• Run Rserve and connecting Tableau:
https://www.lynda.com/Tableau-tutorials/Run-RServe-connecting-Tableau/553698/591408-4.html
• Why integrate R and Tableau?:
https://www.lynda.com/Tableau-tutorials/Why-integrate-R-Tableau/553698/591404-4.html
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3. Optimisation with R

According to the resources, the following methods are common for optimization processes in R:
1) optimize() is devoted to one dimensional optimization problem.
2) optim(), nlm(), ucminf() (ucminf) can be used for multidimensional optimization problems.
3) nlminb() is used for constrained optimization problems.

The following is a list of resources I found useful for doing optimization in R:
-Optimization (with some "Unconstrained, Equally Constraint, General Non-Linear" Optimization and
"Linear Programming" examples):
http://www.di.fc.ul.pt/~jpn/r/optimization/optimization.html
• Optimization using optim() in R (with the 1st example of the "Sphere" function. Others are quite
complex):
https://statacumen.com/teach/SC1/SC1_17_optim.pdf
• How to use optim in R (with two simple "Minimise residual sum of squares" and "Maximum
likelihood" examples):
http://www.magesblog.com/2013/03/how-to-use-optim-in-r.html
• Optimization using the optim function (with the 1st two examples on the 1 and 2 dimensional
problem optimizations. Others are complicated):
http://www.ime.unicamp.br/~cnaber/optim%202.pdf
• Constrained optimization in R (a simple example):
https://stackoverflow.com/questions/5436630/constrained-optimization-in-r
• An almost comprehensive resource about Optimization in R with useful examples. Some of which
are quite baffling:
http://zoonek.free.fr/blosxom/R/2012-06-01_Optimization.html
• A simple optimization example in R (using the "solnp()" function):
https://stackoverflow.com/questions/18759854/how-to-solve-a-simple-optimization-in-r
• Classic "optim()" and "constrOptim()" functions definitions with examples:
https://stat.ethz.ch/R-manual/R-devel/library/stats/html/optim.html and
https://stat.ethz.ch/R-manual/R-devel/library/stats/html/constrOptim.html
• R Programming/Optimization (with some simple optimization examples):
https://en.wikibooks.org/wiki/R_Programming/Optimization

------------------------------------------------------------------------------------------------

video resources:
• Constrained optimization in R: https://www.youtube.com/watch?v=MCvz-c6UUkw
• Introduction to R: Numerical Optimization: https://www.youtube.com/watch?v=j0jmuEXUqyM
• Portfolio Optimisation with R: https://www.youtube.com/watch?v=XMr8CMilrF8
• Contemporary Portfolio Optimization Modeling with
R: https://www.youtube.com/watch?v=rZcPSGoSnDQ
• Constrained optimization in R: https://www.youtube.com/watch?v=sAKj2GT26FY
• Optimization Application in R: https://www.youtube.com/watch?v=4M5wHzCzUyc
• Solving systems of linear equations - Statistical Programming Language
R: https://www.youtube.com/watch?v=jF71LzipydA

-------------------------------------------------------------------------------------------------

Some extra (somewhat more complicated) examples of Optimization with R:
• Linear programming in R: an lpSolveAPI example:
https://www.r-bloggers.com/linear-programming-in-r-an-lpsolveapi-example/
• Bayesian Optimization of Machine Learning Models:
https://www.r-bloggers.com/bayesian-optimization-of-machine-learning-models/
• Online portfolio allocation with a very simple algorithm:
https://www.r-bloggers.com/online-portfolio-allocation-with-a-very-simple-algorithm/
• Genetic algorithms: a simple R example:
https://www.r-bloggers.com/genetic-algorithms-a-simple-r-example/

interesting article (maybe for those who want to dig more):
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• A conversation with John Nash about optim and
optimx: https://www.ibm.com/developerworks/library/ba-optimR-john-nash/
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4. Visualisation in R

• Five Interactive R Visualizations With D3, Ggplot2, & Rstudio:
https://moderndata.plot.ly/interactive-r-visualizations-with-d3-ggplot2-rstudio/
• Why use R when you have Tableau? Tableau vs. R? An interesting comparison of Tableau vs. R:
http://nandeshwar.info/data-science-2/tableau-vs-r/
• The best R package for learning to “think about visualization”:
http://sharpsightlabs.com/blog/r-package-think-about-visualization/
• Top 50 ggplot2 Visualizations - The Master List (With Full R Code):
http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
• What are some cool examples of data visualization done in R?
https://www.quora.com/What-are-some-cool-examples-of-data-visualization-done-in-R
• Is R a good choice for data visualization for a website?
https://www.quora.com/Is-R-a-good-choice-for-data-visualization-for-a-website
• Comprehensive Guide to Data Visualization in R:
https://www.analyticsvidhya.com/blog/2015/07/guide-data-visualization-r/
• R-analyst Cheat sheet: Data Visualization in R (similar to the previous one but in a concise form):
https://www.analyticsvidhya.com/blog/2015/08/cheat-sheet-data-visualization-r/
• Visualizing Big Data with R (with an impresive presentation):
https://beta.rstudioconnect.com/jmcphers/datavis-talk/datavis.html
• R Shiny v Tableau: Dawn of Graphics:
https://www.linkedin.com/pulse/r-shiny-v-tableau-dawn-graphics-anand-gupta
• Visualizations: Comparing Tableau, SPSS, R, Excel, Matlab, JS, Python, SAS:
http://www.datasciencecentral.com/profiles/blogs/visualizations-comparing-tableau-spss-r-excel-matlab
• Interactive visualization with R-Shiny versus with Tableau -Part 1:
http://datascience-enthusiast.com/R/R_shiny_Tableau_treemap.html
• Graphs: Comparing R, Excel, Tableau, SPSS, Matlab, JS, Python, and SAS:
http://blogs.sas.com/content/sastraining/2016/12/20/graphs-comparing-r-excel-tableau-spss-matlab-js-python-and-
sas/
• 7 Visualizations You Should Learn in R:
https://www.r-bloggers.com/7-visualizations-you-should-learn-in-r/
• What could R programming visualise that Tableau couldn't?
https://www.quora.com/What-could-R-programming-visualise-that-Tableau-couldnt
• Interactive visualizations with R - a minireview:
https://ouzor.github.io/blog/2014/11/21/interactive-visualizations.html
• Great R packages for data import, wrangling and visualization:
http://www.computerworld.com/article/2921176/business-intelligence/great-r-packages-for-data-import-wrangling-
visualization.html
• An open course for Data Visualization with ggplot2:
https://www.datacamp.com/courses/data-visualization-with-ggplot2-1


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