ROADMAP to becoming a Data Analyst in 2024
Summary
TLDRIn 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
📊 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.
📈 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.
Mindmap
Keywords
💡Data Analyst
💡Excel
💡SQL
💡Python
💡Data Visualization
💡Tableau
💡Power BI
💡Basic Math and Statistics
💡Projects
💡Communication
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
YouTube algorithm please to share this
video among all your friend Circle who
might find this video useful and
subscribe to the channel for more
interesting content like this see you
again soon with another interesting
video bye
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