Nerd 101 #2: Learn an analysis coding language

If you're looking for a well-paid job in this digital age, below are the top 3 languages that you should master.

1. SQL (Structured Query Language) - Basic database language that you must know! Based on the majority of Indeed job descriptions, SQL is the number 1 demanding skill set that most employers are looking for in a candidate. The language is very simple and straightforward! People usually use it to retrieve data from different databases and manipulate the data for further analysis.
Some variations of SQL are NoSQL, PostgreSQL, MySQL and Microsoft SQL. SQL is also similar to other languages in Linux systems such as Pig and Hive, which are commonly used in managing big data (Apache Hadoop).
w3school is a perfect site to start learning about SQL. 

2. R - my favorite statistical programming language by far. This language is pretty new compared to SAS but it is becoming very popular. R is open-sourced and it has great community of users online called R-Bloggers. Greatest feature about R is the ease to install and the abundant amount of packages you can explore. Some interesting packages are:

• TwitteR - text mining on Twitter 

• forecast - timeseries modelling

• SQL-related (RPostgreSQL, RMySQL, RODBC) - you can use SQL commands in R

• ggplot2 - fancy graphs and charts

• randomForest - model comparison (machine learning)

You can use R code in many analytics software such as Knime (data mining), Pentaho (business intelligence) and Alteryx (data blending). From my experience, 5-line command in SAS is usually equivalent to 1-line command in R. Why not make life easier?

3. SAS - a powerful programming language and statistical analysis package. SAS has its own rules of syntax so it may be hard to pick up. The software itself is very expensive and hard to install. But once you have the program set up and learn the basic of the language, SAS has many amazing functions.

• SAS Studio - statistical analysis

• Sentiment Analysis Studio - text mining

• JMP - business forecasting

SAS is heavily used in financial, retail and transportation industries. Know your industry well and apply this tool to solve any business problems.

Be Sassy!