STEP BY STEP PROCEDURE AND SKILLSET TO BECOME A DATA ANALYST IN 3 MONTHS IN 2021
As technology grows day by day, the data also grows extensively. It created a lot of opportunities and job openings in today’s job market. In this article, we are going to see about step by step procedure and skillsets to become a Data Analyst. Before diving into the topic, one should understand who is Data Analyst.
Who is Data Analyst?
Data Analyst is the one who does extensive exploration in data, finding insights from the data and present in the form of dashboards or reports to the stakeholder for better decision making and organization growth.
Data Analyst skillset:
There are certain skillsets for Data Analyst. By following those skillsets constantly with dedication one can become a Data Analyst.
- Excel
Excel is a very good data analyzing and crunching tool till date widely used by many Data Analysts and Data Scientists to analyze the small and medium amount of data.
The important functions and features used by Data Analyst in Excel are
1. Data filters and functions
2. Formulas
3. Charts and Plots
4. Pivot table
5. VBA macros
6. Vlookup.
Take 1 week to study these basic concepts and do some mini projects in Excel.
Resource: https://www.youtube.com/channel/UC8uU_wruBMHeeRma49dtZKA
2. Statistics
After learning the basics of excel, next focus on statistics. Statistics is important because one can easily understand the distribution of data, the relationship between the data, outliers detection, etc. Take 1 week to study these basic concepts of statistics.
Resource:
https://www.youtube.com/playlist?list=PL1328115D3D8A2566
https://www.youtube.com/user/joshstarmer
3. BI Tools
From the 3rd to 5th-week focus on BI tools. It turns data into actionable Business Information. We can create interactive dashboards and reports for the stakeholders for better decision making. There multiple BI tools. I mention some of them
1. Tableau
2. Power BI
3. Qlik View
It is enough to be strong with any one of the BI tools. Others are similar to each other.
Resource:
https://www.youtube.com/playlist?list=PL6_D9USWkG1C4raCOTlTf_oq4XnNNNtm9
https://www.youtube.com/playlist?list=PL6_D9USWkG1Bn9Zv53ryWtPczn_05t3rG
https://www.youtube.com/watch?v=gm6oy3fn47w&list=PL6_D9USWkG1CCfnse95uLfhTWPtUv1vLP
4. Python
After learning the basics of BI tools, focus on Python programming language for the next two weeks. Don’t get afraid of hearing the word programming. Python is very easy to learn. Its syntax is like English only even a high school student can learn it. It is an important tool for analytics because it contains lots of Data analytics and Data science libraries that you can use.
The important basic topics in python are:
1. Variables
2. Operators
3. Conditional and Looping statements
4. Functions
5. List and Tuples
6. Sets and Dictionary
7. File handling
8. List Comprehension.
Resource:
https://www.youtube.com/watch?v=hEgO047GxaQ&list=PLsyeobzWxl7poL9JTVyndKe62ieoN-MZ3
https://www.youtube.com/watch?v=eykoKxsYtow&list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0&index=1
5. NumPy, Pandas, and Visualization Packages in Python:
The next two weeks focus more on learning important data analysis packages called NumPy, Pandas, Matplotlib, and Seaborn. These are the fundamental and base topics in Data analysis that everyone should learn.
NumPy — used for creating arrays and matrices, some numeric scientific calculations, Linear algebra calculations.
Pandas — for reading files, creating data frames, and data manipulation work.
Matplotlib and Seaborn — for visualization purposes like creating different types of charts to understand data better.
Resource:
Numpy-https://www.youtube.com/watch?v=rN0TREj8G7U&list=PLUcmakntVocWGSKXIsUn1J7Wm9ekpZ87G
Pandas — https://www.youtube.com/watch?v=CmorAWRsCAw&list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy
Matplotlib — https://www.youtube.com/watch?v=qqwf4Vuj8oM&list=PLeo1K3hjS3uu4Lr8_kro2AqaO6CFYgKOl
Seaborn — https://www.youtube.com/watch?v=MGOcVAOuXxo&list=PL6_D9USWkG1Bu9oQHvqAeurX-hhq_mZNi
https://www.youtube.com/watch?v=XezfbWlEVwE
After learned these packages, go to Kaggle and refer to some notebooks, download any dataset and implement on your own to get experience. Without practice, you cannot succeed in your life. Do practice regularly.
Kaggle notebooks — https://www.kaggle.com/notebooks
Kaggle datasets — https://www.kaggle.com/datasets
6. SQL- Structured Query Language
In the 10th,11th, and 12th week, learn SQL. A Data Analyst needs SQL in order to handle structured data. This structured data is stored in relational databases. Therefore, in order to query these databases, a data analyst must have a good knowledge of SQL. Therefore, when dealing with various Big Data tools, you will make use of SQL
Resource:
kudavenkat playlist (first 16) : https://www.youtube.com/playlist?list=PL08903FB7ACA1C2FB
khan academy SQL course: https://www.khanacademy.org/computing/computer-programming/sql
7. Soft Skills:
Only learning technical skills will not help you to land your dream job. You should have some great soft skills like Group learning, Team Management, Storytelling, Communication, etc.
Do the above-mentioned things regularly and continuously with hard work and dedication. Enjoy your learning when you are learning. It will create a greater impact on you. I hope this article will be useful for aspiring Data Analysts. All the best.
Learn well and Grow well!!!