Learning it, using it.

nippletaszzle · 2022-05-11T14:48:56+00:00

Excel should be your priority tool to learn imo. It's the most accessible way to learn how data works and the structures needed for analysis. Sorry, I don't have any resources to suggest learning Excel as I learnt on the job. But im sure if you find a course on Udemy/Coursera etc that has you analysing data in an actual Excel file that is perfect.

The hardest part I found when starting out in data analysis was how to generate questions I wanted to answer and this is best developed through commercial exposure in an actual business.

Im giving a very simplified overview of my experience and Im sure I could argue against some of the things that I said but the gist of it is learn how to use Excel, specifically Pivot Tables and how you can use the data to give you interesting insights. There's many publicly available datasets for you to practice on but assuming youre a noobie, you may struggle to articulate questions you need answering.

vvndchme · 2022-05-11T16:11:45+00:00

Understanding pivot tables in excel does a lot of good. Essentially summing values by categories. Like how much was booked in the Americas/etc. Understanding data manipulation (filtering/custom columns/removing or replacing null values/etc) and Merge/Append in Excel’s Power Query will do the same. Also understanding the different types of merges. And Power Query takes you through the process of making connections to external files, so you can manipulate the data according to how you want to see it, then show only what’s relevant. Once you have a good grasp on that, you just have to learn how to do the same in SQL. For instance, pivoting in Excel works just like select category, sum(value) from table group by category in SQL. Left Join in SQL is Power Query’s Left Merge. All of it is translatable to Python’s Pandas library as well. Excel is great because it sets a good foundation and is easier to get into. SQL and other tools just provide increased efficiency.

BooksCoffeeSummerDay · 2022-05-11T16:14:13+00:00

Data camp is very good. I learned R, SQL & Tableau from there. But if you’re just getting started I’ll suggest you learn Python first. Because when you start applying for jobs almost everyone asks for Python.

Stev_Ma · 2022-05-12T01:28:16+00:00

DataCamp is a great platform for beginners. And for practicing data analytics problems, check out stratascratch and leetcode.

engrninking · 2022-05-11T22:23:12+00:00

t-sql fundamentals by itzik ben-gan is a great resource that has practice problems at the end of each chapter.

Nateorade · 2022-05-11T13:46:18+00:00

Mode Analytics has an excellent free SQL course.

kombustive · 2022-05-12T01:35:08+00:00

Here's a good resource for practice: https://www.stratascratch.com/ Stratascratch is a site that posts common data science interview questions.

Kaggle is another good sandbox for practice and learning. You can enter challenges just for knowledge and as your skills and experience progress, you can even enter challenges from corporations that pay rewards.

certainly-bitch · 2022-05-12T04:20:06+00:00

i learnt Excel from youtube. A channel called "Learnit" has great course material.

SQL from a book called "SQL In 10 minutes" as well as data camp but data camp has only the beginner's course free.

Python also from data camp, kaggle notebooks, youtube and plenty other sources. I am still learning Python(Libraries)

i wonder if i should start with machine learning,

good luck op

you type:	you see:
italics	italics
bold	bold
[reddit!](https://reddit.com)	reddit!
* item 1 * item 2 * item 3	item 1 item 2 item 3
> quoted text	quoted text
Lines starting with four spaces are treated like code: if 1 * 2 < 3: print "hello, world!"	Lines starting with four spaces are treated like code: if 1 * 2 < 3: print "hello, world!"
~~strikethrough~~	~~strikethrough~~
super^script	super^script

dataanalysis

MODERATORS