ROADMAP to becoming a Data Analyst in 2024

Summary

In this video, Sandep shares a cost-effective roadmap for aspiring data analysts in 2024, emphasizing that a traditional master's degree and significant investment are no longer prerequisites. He suggests starting with mastering Excel, followed by SQL, Python, and data visualization tools like Tableau or Power BI. Sandep also stresses the importance of understanding basic math and statistics. He recommends building projects to solidify learning and showcase skills, and encourages communication of these projects to simulate real-world data analyst roles.

Takeaways

• 🎓 Becoming a data analyst in 2024 doesn't require a significant financial investment; resources like YouTube and ChatGPT can facilitate learning.
• 📈 Data analysis is a valuable skill across various sectors including healthcare, finance, retail, technology, and sports, indicating a consistent demand.
• 💼 The top skills required for data analysts are SQL, Excel, Python, Tableau, and Power BI, as identified from job postings.
• 📊 Excel is crucial for data analysts as it's commonly used by business teams and stakeholders for discussing data and insights.
• 🗝️ SQL is fundamental for data analysts, as it's the language used to communicate with databases, and is present in nearly all job postings.
• 🐍 Python is not mandatory but is highly beneficial for automating tasks, data cleaning, and setting up pipelines in data analysis.
• 📊 Data visualization skills are important for presenting analysis and insights to stakeholders, with Tableau and Power BI being popular tools.
• 📊 Understanding data visualization concepts is essential before mastering specific tools, as it guides the choice of appropriate charts and graphs.
• 🧮 A solid grasp of basic math and statistics is necessary for data analysts to perform effective data analysis.
• 🔨 Building projects is an effective way to learn and showcase data analysis skills, starting with personal life projects and then moving to real-world datasets.
• 📢 Communication of data analysis findings is crucial, which can be done through written formats like LinkedIn posts or videos on platforms like YouTube.

Q & A

What is the main message of the video regarding becoming a data analyst in 2024?

The main message is that becoming a data analyst in 2024 is feasible with minimal investment, primarily through learning resources available on platforms like YouTube and ChatGPT.

What are the top five skills identified in the video as essential for a data analyst?

The top five skills are SQL, Excel, Python, Tableau, and Power BI.

Why does the speaker emphasize the importance of Excel for data analysts?

Excel is emphasized because it is a basic spreadsheet tool that is commonly used by business teams and stakeholders for discussing numbers, trends, and patterns, making it a go-to tool for sharing analysis and findings.

What is the significance of SQL in the role of a data analyst according to the video?

SQL is significant because it is the language used to communicate with databases, data warehouses, or data lakes, and is essential for performing data analysis tasks such as building reports or dashboards.

Why is Python recommended as a programming language for data analysts?

Python is recommended because it is powerful and used for tasks like data automation, cleaning, transformation, and setting up pipelines, which are important for advancing data analysis skills.

What are the two advantages of building projects as mentioned in the video?

The two advantages are active learning through application of concepts and showcasing skills on platforms like resumes, LinkedIn profiles, or portfolio websites.

How does the speaker suggest one should start with project ideas for data analysis?

The speaker suggests starting with personal life projects, such as analyzing personal expenses, and then moving on to real-world datasets from sources like Kaggle and Google datasets.

What is the speaker's recommendation for the learning path to become a data analyst?

The recommended learning path is Excel, SQL, Python, and then either Tableau or Power BI.

Why is basic math and statistics important for data analysts, as per the video?

Basic math and statistics are important because they form the foundation for understanding and applying concepts like averages, median, standard deviation, percentage difference, and probabilities during data analysis.

What does the speaker suggest as a method to enhance the learning experience in data analysis?

The speaker suggests using real-world data sets that are of personal interest, such as sports or finance data, to make the learning process more enjoyable and easier.

How does the speaker propose to communicate the results of data analysis projects?

The speaker proposes communicating the results through written formats like LinkedIn posts or Medium articles, or spoken formats like YouTube videos, to simulate a real-world data analyst role.

Outlines

00:00

📊 Becoming a Data Analyst in 2024

The speaker shares their journey of becoming a data analyst after completing a master's degree and investing $50,000 and two years. They emphasize that in 2024, one can become a data analyst with zero investment using resources like YouTube and ChatGPT. The video aims to provide a roadmap for starting a career in data analytics. The speaker, Sandep, discusses the demand for data analysts across various sectors and the importance of skills like SQL, Excel, Python, Tableau, and Power BI. Sandep suggests starting with Excel and SQL, as they are foundational for data analysis, and then moving on to Python for more advanced tasks. The video also touches on the importance of data visualization tools and the need for a basic understanding of math and statistics.

05:01

📈 Skills and Project Building for Aspiring Data Analysts

The second paragraph delves into the specifics of data visualization, emphasizing the need to understand when to use different types of charts and the basics of data visualization concepts. The speaker recommends starting with a week of learning these concepts before moving on to tools like Tableau or Power BI. They also stress the importance of basic math and statistics for data analysts, suggesting that a solid understanding of concepts like averages, medians, standard deviations, and probabilities is crucial. The paragraph concludes with advice on building projects to apply and showcase newly acquired skills. Sandep suggests starting with personal life projects for ease of learning and enjoyment, and then progressing to real-world datasets for a more comprehensive understanding. The speaker also encourages communication of these projects through various formats to simulate a real-world data analyst's role.

Keywords

💡Data Analyst

A data analyst is a professional who collects, processes, and interprets complex digital data, using various tools and techniques to derive insights that can inform business decisions. In the video, the speaker emphasizes the growing demand for data analysts across sectors like healthcare, finance, retail, technology, and sports. The role involves analyzing data to improve business value and make stakeholders happy, highlighting the importance of data analysis in the modern business landscape.

💡Excel

Excel is a widely-used spreadsheet tool that is fundamental for data analysts. It allows for data organization, manipulation, and visualization. The video script mentions Excel as the first skill set for a data analyst because it is often the medium through which analysis and findings are shared with business teams and stakeholders. The speaker suggests that mastering Excel is a prerequisite for learning SQL, as it provides a foundation for understanding data structures and manipulation.

💡SQL

SQL, or Structured Query Language, is a programming language used for managing and manipulating databases. The video underscores SQL as a fundamental skill for data analysts, essential for communicating with databases, data warehouses, and data lakes. The speaker notes that SQL is the 'ABC' of data analysis, and proficiency in it is crucial for performing tasks like data analysis, report building, and dashboard creation.

💡Python

Python is a versatile programming language that is increasingly popular in data analysis due to its simplicity and powerful libraries for data manipulation and analysis. The video script suggests that while Python is not a mandatory skill, it enhances a data analyst's capabilities, particularly for tasks like data automation, cleaning, transformation, and pipeline setup. The speaker's experience indicates that Python is becoming more prevalent in the field.

💡Data Visualization

Data visualization involves the graphical representation of information and data, making it easier to understand and communicate insights. The video highlights the importance of data visualization tools like Tableau and Power BI for presenting analysis and insights to stakeholders. The speaker prefers Power BI for its similarity to Excel, which can be advantageous for those already familiar with Excel formulas.

💡Tableau

Tableau is a leading data visualization tool that allows users to create interactive and shareable dashboards. The video mentions Tableau as one of the top data visualization tools, with a 24% occurrence in job postings. It is often preferred in roles that require creating dashboards, and the speaker suggests learning Tableau as part of the recommended skill set for aspiring data analysts.

💡Power BI

Power BI is a business analytics service by Microsoft that enables users to visualize data, create reports, and gain business insights. The video script positions Power BI as a popular alternative to Tableau, with a 20% occurrence in job postings. The speaker personally prefers Power BI due to its integration with other Microsoft tools and its user-friendly nature for those familiar with Excel.

💡Basic Math and Statistics

Basic math and statistics form the backbone of data analysis, involving concepts like averages, medians, standard deviations, percentages, and probabilities. The video emphasizes the need for a solid understanding of these concepts as they are integral to the analysis process. The speaker suggests that these skills are essential for interpreting data and drawing meaningful conclusions.

💡Projects

Projects are practical applications of data analysis skills, allowing individuals to apply concepts in real-world scenarios. The video script advocates for building projects as a way to learn and showcase data analysis skills. The speaker suggests starting with personal life projects, such as tracking expenses, and then moving on to public datasets for more complex analyses. Projects help in active recall of concepts and provide a platform to demonstrate expertise.

💡Communication

In the context of the video, communication refers to the ability to effectively convey data analysis findings, either through written or spoken formats. The speaker stresses the importance of communication skills for data analysts, as they need to present their insights to various stakeholders. This can involve writing reports, creating LinkedIn posts, or even producing YouTube videos to simulate real-world data analyst roles.

Highlights

Becoming a data analyst is possible with zero investment using YouTube and ChatGPT in 2024.

Data analysis is a valuable skill across multiple sectors including healthcare, finance, retail, technology, and sports.

The demand for data analysts remains constant as long as there is data to analyze.

Top skills required for data analysts include SQL, Excel, Python, Tableau, and Power BI.

Excel is crucial for sharing analysis and findings with business teams and stakeholders.

SQL is the foundation for communicating with databases and is essential for data analysts.

Python is a powerful tool for data cleaning, transformation, and automation in data analysis.

Data visualization skills are important for presenting analysis and insights to stakeholders.

Tableau and Power BI are popular tools for creating data visualizations and dashboards.

Basic math and statistics are necessary for understanding data analysis concepts.

Building projects is an effective way to learn and showcase data analysis skills.

Personal life projects can be a good starting point for learning data analysis.

Public datasets from websites like Kaggle and Google can be used for real-world data analysis projects.

Communication skills are vital for data analysts to effectively share their findings.

Writing articles or creating videos can help simulate the real-world role of a data analyst.

The recommended learning path for a data analyst includes Excel, SQL, Python, and data visualization tools.

The video provides a roadmap for starting a data analysis career from scratch.

Transcripts

I became a data analyst after doing my

masters in us and spending $50,000 and

entire 2 years but you don't need to do

that in 2024 you can become a data

analyst with zero investment with just

YouTube and chat gbd BEC a data analyst

might look difficult from the outside

but trust me it's not that difficult

watch this video fully to find out the

exact road map that I would take if I'm

going to start my data analy career from

scratch let's di in welcome back guys my

name is sandep and if you're new to the

channel I talk about stuff like job

search to your for Masters and this is

my first attempt at talking about data

analytics becoming a data analyst worth

it in 2024 companies always have a lot

of data it's going to lie somewhere in a

database or data warehouse so without

analyzing the data the compan is not

going to know how to improve the

business increase the business value

make the investors happy I feel there's

always constant demand for data analysis

across multiple sectors like healthcare

Finance retail technology or even Sports

data analysis is not going to go away as

long as that is data my opinion is it's

not too late to become a data analyst in

2024 what kind of skill set do you need

this is a chart from Luke baros so he

has literally scanned like almost

500,000 job postings and extracted the

keywords present in it so clearly if you

see the top five are SQL Excel python

Tableau P I'm going to just focus on

these five that's what is going to occur

in most of the job posting so first

skill set is obviously the sprad sheet

tool it can either be Excel or Google

sheet I'm talking about this first

before SQL is because SQL is more like a

advanced form of excel so if you get

your Excel skills strong then SQL will

become a lot easier you may be thinking

how is Microsoft Excel which is a basic

spreadsheet tool important for being a

data analyst the reason is a lot of the

business teams or stakeholders they're

not going to go talk about technical

stuff the things they talk about is

numbers Trends patterns insides the

medium they use Excel or Google sheet

and hence Excel is going to be the go-to

tool for sharing all your analysis and

findings to the business team and

stakeholders probably everyone of you

might have used excel at one point in

time so it's not going to be that

difficult to pick it up just go to

YouTube and watch a 1 Hour Quick crash

course video and then start applying

those Concepts maybe track your fitness

goals or your expenses or anything from

your daily life remember that the best

way to learn is by doing and not by just

seeing videos next I'm going to talk

about SQL which according to data occurs

in almost like 47% of the job posting

which I feel is too low because SQL

should be there in probably all the job

postings SQL is like the ABC of being a

data analyst that's the language you'll

be using to communicate with the

databases or data arouses or data laks

and without learning the basics of SQL

you cannot become a good data analyst

ask data analyst what You' be ask us

you'll be getting some requirements from

the business uh stakeholders asking you

to do some analysis or build reports or

dashboards you would have to use SQL for

it I recently interviewed for the last 3

months after layoff and almost like 10

to 15 interviews 80% of the technical

interviews were just based on SQL the

remaining was python or PBI or Tableau

just learning the SQL Basics shouldn't

take more than 2 weeks and I think

YouTube has a lot of good courses I'll

attach the links in the description

obviously you can go to UDI or Kosar as

well you can use chat gbt to speed up

your learning process like you can just

ask chat gbt to give the concepts for

studying the SQL Basics to become a

analyst and then you can ask it to

explain it with examples okay next you

need a programming language like python

r r I'm going to stick to python first

because uh that's more easy and that's

what is mostly going to be used by the

companies this is my third company in us

and in the previous two companies I

never used python but now I'm using

python it's not a mandatory skill but to

take your data analytics skills to the

next level and up your game you would

certainly need python because python is

extremely powerful as data analyst you

would be asked to do some automations

perform data cleaning data

Transformations and setting up pipelines

you would certainly need python during

that times for python there are a lot of

resources on YouTube so how I learned

python was I did a udmi course which was

python for data analytics and data

science I'll attach the link to the

description and uh as I said use jib to

speed up the learning process the other

skill that you lead as a data analyst is

your data visualization skills now all

the roles don't require the skill

because you would not be creating

dashboards in all the data analysis

roles after you done all the analysis

and insights you would certainly need to

present it to some stakeholders as I

said you you would probably be using

Excel sometimes but for some of the

projects and in some of the companies

maybe your data Vis tool is a preferred

form of communication so you would be

building a tableau a prob a dashboard

tblo with 24% and power B with 20% are

the most popular data visualization

tools out there and you can certainly

choose anyone uh to learn Al so tblo

seems a bit more popular but I certainly

prefer powerbi because it's a Microsoft

offering I find it a lot similar to

Excel and so if you know Excel formulas

you can kind of translate that to

powerbi but before you go into the tools

itself understand the data Vis Concepts

when to use bar charts verus line charts

what is histograms and what is cat plots

just to get your Basics covered first it

shouldn't take more than a week and then

you can move on to any tool like Tableau

or pobi I'm going to attach the corer

Andi course links for tblo and pobi the

path I would recommend is if I'm going

to start over as a again is Excel SQL

python b or Tableau and that's going to

complete the text tag that's one more

skill that you would need to know to

become a good data analyst that is basic

math and statistics because you would

not be using like calculus or linear

algebra and those kind of Concepts

probably using like averages median

standard deviation percentage difference

probabilities those are the concepts

that you be using you need to have a

solid understanding of these Concepts

you would be certainly using these

Concepts during the analysis itself once

you're done with the preparation which

is probably going to take like 2 months

it's time to apply doing or taking

action is the best form of learning

something and the best way to learn is

obviously build projects building

projects has two advantages according to

me one is you're going to learn because

uh when you're applying all the concepts

you're going to do the active recall the

second thing is obviously we want to

showcase our skills either on your

resume or LinkedIn profile or even maybe

a portfolio website for project ideas

you can go to chat gbd and ask for

project ideas but if you ask me I would

certainly recommend to first start with

your personal life projects you can dig

into your own life look at maybe your

expenses over the one year taking every

day uh for example like during my layoff

I track my own job applications and then

showcase that in a form of a dashboard

so I personally find this a great way to

learn because if you're looking into

your own life rather than a real world

data set it's a lot easier and more

enjoyable to learn and to take it one

level further you can look at websites

like gagle and Google data sets so

you'll be getting a lot of real world

data sets like for example Netflix stock

prices or if you're interested in

cricket you can get some Cricket data

like IPL data so just choose any data

set which are most interested in public

in healthcare or Finance try to analyze

it and then showcase it in the form of a

dashboard do like four to five projects

initially once you do it obviously as a

data analyst you need to communicate

it's not just like speaking it can be

even writing writing a LinkedIn post or

a medium article or even doing a YouTube

video but once you're done communicate

that in a written format or in a spoken

format like a YouTube video that will

give you a end to endend simulation of

how a data analyst rule looks like in

the real world hopefully you found value

in this video if you do have any

questions or if you have any feedback

please let me know in the comment

section I'll certainly take a look and

provide my answers and opinions please

check out my previous video where I have

talked about if 2024 is the right time

to come to us for Masters and kindly do

like the video that's going to help the

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interesting content like this see you

again soon with another interesting

video bye