Do you want to become a data analyst or data engineer in 2022? Data-related roles such as data analysts, data scientists, data engineers, and data architects are booming and IT companies are flocking to recruit skilled people for these roles. As we know, Data Analysts and Data scientists are the buzzwords of the present day and one of the main attractions of this role is the pay and growth component. With so much data being collected every second, data experts are in high demand today.
In this article, we are going to talk about one of the exciting careers in data which is a data analyst. We will talk about how to become Data Analyst or complete the roadmap to becoming a Data Analyst in 2022. So let’s start the article without wasting any time:-
A Data Analyst is responsible for collecting, processing, and analyzing data to find informed insights to help businesses make smart decisions.SQL, Excel, and data visualization tools (such as Tableau, and PowerBI) are used to create visualizations and reports that simply describe the current data environment. A data analyst uses several tools to process and work with data. Experience working with various tools and statistics is most important to him.
In other words, a data analyst is a person who turns that raw data into intelligence to gain meaningful and actionable insights. These insights are then used to help businesses make smart decisions. And these insights are then used by companies in a variety of ways, from shaping marketing strategies to improving manufacturing processes.
I have divided this roadmap into 11 steps so that you can easily learn these skills. I have mentioned all the topics that you should definitely learn to become a data analyst in 2022. You can learn these skills free of cost on google and youtube because all the topics are given on google. I have not described each topic only I have mentioned the topics that you should learn for data analysis.
If you want to become a data scientist or data analyst then excel is one of the basic skills to learn in this field. Excel is a compulsory skill for data analysts because there is a vast use of excel.
These are the topics that you must know:
- Pivot table
If you want to become a Data Analyst so you should learn Google Sheets because with the help of Google Sheets you can do data entry, data management, accounting, and analysis.
These are the topics for Google Sheets:
- How to Create Google Sheets?
- Selecting cells
- Perform functions
- Copying function
- Move cells
- Undo and Redo
- Relative References
- Absolute References
- How do Gridlines work?
- Ascending and Descending
Now the third skill but most important skill is SQL(Structured Query Language) which is used to INSERT, UPDATE and DELETE data into a database using the query. SQL is one of the important skills for Data Science or Data analysts and it is also necessary for web development and other fields. You must know this skill because it is available free of cost on the internet, just go on google and search SQL tutorial and learn it.
These are basic topics for SQL:
- Select and Select Distinct Query
- Where, And, Or & Not Query
- Order By and Group By Query
- Insert Into, Update, Delete Query
- Min and Max, Count, Avg, Sum Query
- Like Query
- Union Group By
- Create DB, Drop DB
- Create Table, Drop Table
- Unique Key, Primary Key, Foreign Key
- SQL Joins
- Inner Join
- Left Join
- Right Join
- Full Join
- Self Join
If you are trying to become a good Data Analyst then you must know one of the programming languages like Python or R or SaaS but in my point of view, Python will be the best choice for Dat Science or Data Analyst. If you know python then you can simply switch to the Web development field just learn Django or Flask if you want to switch. As I have created a complete roadmap for python previously, you can simply click on Roadmap to Learn Python and learn this skill.
- Roadmap to Learn Python
- Introduction of Python/R Programming
- Basics Concepts
- Data Structure in Python/R
- Functional Programming
- Exception Handling
- File Handling
- Advance Concept
- OOps Concepts
One of the best libraries on python programming is Numpy as Numpy is used in every field like in Data Analyst, Data Science, Machine learning, or Deep Learning. Before starting the data analyst tutorial just learn Numpy and it is available on google free of cost so on there to learn this skill.
These are the basic topics of Numpy:
- Introduction to Numpy
- Array Sort
- 1D and 2D array creation
- Multidimensional array
- Indexing and Slicing
- Attributes of a NumPy array
- Array Manipulation functions
Pandas library is used for storing data, cleaning data, and wrangling data. Pandas is one of the most used libraries of python programming to store data in CSV files, JSON files, or excel files. With the help of the panda’s library, you can simply represent list or dictionary data into tables. So pandas library is very important for data analysts or data science.
These are the basic topics of the panda’s library:
- Pandas Introduction
- Pandas Data Structure
- Series in Pandas
- DataFrame in Pandas
- Access Elements from pandas element
- Columns, Index, Rows, and Values functions
- Merge multiple files in one
- Merge Multiple files with distinct columns
- head(), tail(), info(), unique() and dropna()
- mean(), median, and mode(), describe()
Matplotlib is a python programming library that is used to represent data into graphs or charts. This stool is used for representing data that you have scraped or cleaned from other sources. Matplotlib is important for Data Science so you must learn this library it is also available on google free of cost so just go and learn this skill.
These are the topics for Matplotlib:
- Introduction to Matplotlib
- Pie Charts
You must know these mathematics topics before digging into data analysis or data science. Mathematics is an important concept of programming if you want to do any big work then you must know these concepts of mathematics.
These concepts are necessary:
- Descriptive stats
- Inferential stats
- Linear algebra
For the data visualization, you will have to learn Tableau or PowerBI tools to represent data in visualization form. Most companies prefer PowerBI but both tools are good for Data Visualization, you must know one of the tools. With the help of these tools, you can simply represent your data in visualization form.
Data Visualization Tools are:
The last and final step is Data Analyst, now you know all the tools that are necessary for Data Analyst. The main task of a Data Analyst is to scrape data or collect data from different sources then clean the data after that extract useful data and use that data in business or any other field.
The main task of a data analyst are:
- How to Collect Data
- How to Clean Data
- Analyzing Data
- Designing and maintaining data systems
- Mining data from primary and secondary sources
- Fixing coding errors
The last step of Data Analyst is to make projects and add those projects to your portfolio or resume. This step is very important for every person who wants to get a job as a data analyst or data science. Before going to give any interview you will have to create some basic projects so that you can show them that I have created these projects using these tools.
I have covered all the topics that you should learn for data analysis. I know you are eager to enter the world of analytics. So this skill is gold for you. Take your time, understand things, practice, solve some problems, and work on real projects and you will be ready to be called a data analyst soon.
Do you have any queries related to This Article, Please mention them in the Comment Section of this Article, We will contact you soon.
Thank you for reading this blog. I wish you the best in your journey in learning and mastering Django.
Follow me to receive more useful content: