How to study to become a Data Analyst?
One of the top jobs in the market and also being among the ones which are higher in demand is the Data Analyst. Is it difficult to become a data analyst? Actually it is not so difficult to become a data analyst. Not more difficult than becoming a front end developer or back end developer. Data jobs have 3 different segmentations.
Data Science
Data Engineer
Data Analyst
These 3 occupations are all related to the data and have slightly different expertise fields. Data has become a necessary field for many companies and as data amount increases with every passing day it also raises the necessity to handle the data amount. But handling this data is not enough, you need someone else to tell the story for the stakeholders. Because looking at the numbers alone is simply not enough.
Difference between the Data Jobs
Now here comes the difference between the 3 different jobs for data. Data Engineer is the one who sets up the environment for the Data Analysts and Data Scientists to work with the data. They have strong knowledge on database systems and cloud technologies. Cloud technologies are especially essential for the data engineers since most of the big companies handle their data on cloud.
Data Scientists are the one who build predictive models using the data. To give some examples, if you don’t know what to search for in the search bar in an online shop, the predictive model brings you the items that are most relevant to your inquiry. Or another example can be the forecast of your sales over the next months.
On the other hand data analysts are the middle person for the stakeholders and the technical staff. Data analysts create compelling stories with the data mainly by using charts for non technical people to comprehend. Their daily activity is mainly on searching for trends, explaining sudden falls or increases in sales, finding the best campaign for your products, setting the best price practices and so on. They do this by using the data handled to them by data engineers and sometimes using predictive models developed by the data scientists on necessary occasions.
Data Analyst Prequests
To become a data analyst you need to learn 4 key technologies. The rest are very similar. But these 4 would make you a data analyst.
- Excel or Google Sheets
- SQL
- Python or R
- Tableau or PowerBI
Excel
Microsoft Excel should be the first program that you should be learning in order to understand the data. The equivalent of this program is the free version of google sheets where you can access simply by logging in with your gmail account. Although it is free, many big companies use google sheets since it has very good cooperation enabled tools. It is very easy to share your documents with your friends, receive comments and work on the same documentation together with your colleagues. So it is also widely used. They are very similar on many occasions. But whichever you pick to learn it doesn’t matter a lot since you need to learn the tabular data format. Learning excel will grant you this understanding which will come in handy when learning SQL database management systems. Because in SQL data is handled in tabular form just like in excel but with a much bigger volume that cannot be processed by excel alone.
SQL
In order to learn SQL there are plenty of documentations for free online. Youtube is already a very good tool for learning SQL efficiently. The basic information for SQL can be learned in 1–2 weeks but what you need is practice. Don’t forget, practice makes perfect. To do practice I would highly recommend leetcode.com You should start by doing easy questions and then move onto medium questions. There are also hard questions but you really don’t need them at all. In almost all of the interview questions that you will come by there will be 1 Easy question and 1 medium question from the SQL. In some companies they might send you 2 medium questions. But if you solve %80 of the medium questions in the leetcode you will have no problem. If Lettcode is not enough for you then you can take a look at the hackerrank.com for some more practice as well. Both places also have a discussion forum where you can see other peoples solutions that can help you understand and you can ask questions. The community in those 2 websites are pretty amazing actually.
Python — R
Now comes the hard part where we start learning Python or R. Which one to pick? If you are a new commer then I would highly recommend python because it has a larger field of usage considering R is only used for data purposes while in python you can use it for many different things like creating a website, compiling a program etc.
On the other hand R is widely used among data scientists. There are plenty of useful packages in R to be used. While in python they can be a little bit more difficult to work.
The bottom line is, while i highly prefer using python in my work, R is also a very useful tool. On python there are also a very big selection of visualisation tools such as seaborn and matplotlib. With these tools you can create any number of visualisations with a few line of code.
Tableau — Power BI
This is the final in the list. On some companies they strictly ask you to use one of the tools but in most cases they ask you if you have used one of those tools so that they can understand if you can make some graph or explain the data using visualisations. I would put these at the bottom of my list. When you cover the other topics then you can take a look. You don’t need to be an expert in these tools to land a job at all, if not asked specifically.
Learning Order :Excel > SQL > Statistics >Python > Tableau
