data analysis with excel for dummies pdf

#Data analysis with excel for dummies pdf how to#
#Data analysis with excel for dummies pdf install#

#Data analysis with excel for dummies pdf install#

If something is missing, please read the article again: Install bash, Python, R and SQL!

Pgadmin4 (or preferably SQL Workbench) on your computer.

PostgreSQL installed on your data server.

A data server with Terminal (or iTerm) access.

If you went through the above-linked article, please double-check that you have these 3 things: I picked postgreSQL because it’s very popular (lots of the online businesses are using it) and it’s said to be the most advanced open source SQL language.

The good news is that all SQL languages are very similar – if you learn postgreSQL, it will be a matter of hours (or even minutes) to adapt to another one. Note: in my “SQL for Data Analysis” articles I’ll use postgreSQL! There are other types of SQL languages (another well-known open source one is mySQL).

#Data analysis with excel for dummies pdf how to#

It’s a step by step tutorial about how to set up your own Data Server and install bash, Python, R and SQL on it. Note: if you have your own SQL environment already, you can skip further to STEP 2 – Get some data!įirst, please go through this article. Spark, Hive, etc.) also support SQL!īut now, let’s jump on the practical part! STEP #0 – Install your own SQL environment to practice! The main differences will be syntax, “features” and performance… But I really don’t want to go into that topic right now, because:Ī) I promised a practical tutorial and that topic is a bit more theoretical (even philosophical)Ĭ) at this level, you don’t have to worry about performance at all – and when you will, most probably a senior data scientist or a data engineer will help you out. Once you start to apply these languages on real life analytics projects, you will see that Python is good for some things and SQL is good for other things. The answer is… well, there is no categorical answer for this question!

If you have done my bash or Python tutorials already, you might ask: is SQL better or worse than Python, R or bash? But you will be able to do these more efficiently and on much larger data sets than before. When you use SQL for data analysis, you will use it (most probably) for simple tasks: aggregating data, joining datasets, using simple statistical and mathematical methods. Here are just two practical advantages: joining tables is much easier in SQL than it is in Excel - and automating and reusing your code will become more convenient with SQL, too. But believe me, once you’ve understood the basics of SQL, you will find it much clearer and more much easier than Excel.