1 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 —————————————- 3 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): 4 • A conversation with John Nash about optim and optimx: https://www.ibm.com/developerworks/library/ba-optimR-john-nash/ —————————————————————————————————- 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
