Do not become a data analyst if.......

Summary

This video script offers a reality check on the expectations of becoming a data analyst. It highlights the necessity for self-learning, patience, and strong communication skills in the role. The speaker dispels the myth of high starting salaries, clarifying that while data analysis can be a rewarding career, it requires persistence and the ability to work independently and with others. The script provides valuable insights for those considering a career in data analysis.

Takeaways

• 🚀 Becoming a data analyst requires a lot of self-learning and independence.
• 📚 If you need a lot of hands-on help, this role might not be the best fit for you.
• 🔄 The field is constantly changing, so ongoing learning is necessary.
• 🔍 You may need to Google and learn tools like SQL, Tableau, and Power BI on your own.
• 🤔 Being able to find answers independently is crucial since coworkers may be busy.
• ⏳ Patience is key, as you'll encounter challenges with databases, tools, and debugging.
• 🤝 Communication is important; you'll interact with team members, stakeholders, and clients.
• 💼 Daily scrums and updating project statuses are part of the job.
• 💬 If you dislike frequent interaction and teamwork, this role might not suit you.
• 💰 The expectation of a high starting salary (like $100k) is often unrealistic for entry-level positions; typical salaries range from $60k to $80k.

Q & A

Why should someone who is not a self-learner avoid becoming a data analyst?

In the role of a data analyst, you need to learn a lot on your own as things are constantly changing. If you require a lot of hands-on help to complete tasks, this may not be the best fit because you must be an independent learner.

What is the importance of self-learning for a data analyst?

Self-learning is crucial for data analysts because they often need to acquire new skills and knowledge on their own, as on-the-job training may be limited. This includes learning tools like SQL, Tableau, and other data visualization tools independently.

What challenges might a data analyst face with databases and tools?

Data analysts might face issues such as debugging code, finding the right data source among hundreds of tables and views, and dealing with tools that don't always function as expected. Patience and problem-solving skills are essential.

Why is patience important in a data analyst role?

Patience is vital because data analysts encounter various issues, such as debugging code, waiting for data or approvals, and handling clients who may change their requirements frequently. These situations require a calm and patient approach.

How does communication play a role in a data analyst's job?

Communication is key for data analysts as they need to interact frequently with team members, stakeholders, and clients. This includes giving project updates, working through roadblocks, and collaborating on solutions.

What might surprise people about the amount of interaction required in a data analyst role?

Many people might expect data analysts to work mostly in isolation. However, the role requires significant interaction with others, including team meetings, client updates, and regular communication to ensure project alignment.

What is a common misconception about the salary of entry-level data analysts?

A common misconception is that entry-level data analysts start with a salary of $100,000 per year. In reality, the average salary ranges from $60,000 to $80,000, with higher salaries typically requiring more experience.

Why should someone research job listings before pursuing a data analyst career?

Researching job listings helps manage expectations about salary and job requirements. It ensures you understand the typical compensation and skills needed in your area, preventing unrealistic expectations about immediate high earnings.

How can someone prepare for the on-the-job learning required in a data analyst role?

Preparing for on-the-job learning involves developing strong self-learning habits, familiarizing yourself with relevant tools and technologies, and practicing problem-solving skills. Taking courses or certifications can also provide foundational knowledge.

What advice does the speaker give to those considering a career in data analytics?

The speaker advises researching job listings to understand the typical salary and requirements, being prepared for significant self-learning, developing patience, and being ready for frequent interactions with colleagues and clients.

Outlines

00:00

📚 The Reality of Becoming a Data Analyst

The speaker discusses the expectations versus reality of being a data analyst, emphasizing that it's not a career path for everyone. They stress the importance of being a self-learner due to the constant need for acquiring new skills independently. They share their own experience of entering the field without prior training in tools like SQL or Tableau, highlighting the necessity of self-education and problem-solving on the job. The speaker advises against relying heavily on colleagues for help, as everyone is typically busy with their own projects.

05:02

😣 The Challenges and Frustrations of Data Analysis

The speaker warns that the role of a data analyst can be frustrating and requires a lot of patience. They describe various challenges, such as debugging code, locating data sources, and dealing with changing client requirements. These frustrations can make the job difficult for those who are easily irritated or impatient. The speaker highlights the importance of persistence and the ability to manage stress when dealing with such issues.

🤝 The Importance of Communication and Teamwork

Contrary to the belief that data analysts work in isolation, the speaker explains the significant amount of communication and collaboration required in the role. They discuss the need for regular interaction with team members, stakeholders, and clients through meetings, updates, and project management tools like Jira. Effective communication skills and the ability to work well with others are crucial for success as a data analyst.

💰 Misconceptions About Salary Expectations

The speaker addresses the common misconception that data analysts can easily earn high salaries right out of the gate. They clarify that while some may achieve high-paying roles, the average starting salary for a data analyst is typically between $60,000 and $80,000. They caution against unrealistic expectations and advise potential analysts to research job listings and salary ranges in their area before investing time and money into certifications or courses.

🔍 Final Advice and Encouragement

The speaker concludes by encouraging viewers to thoroughly research and consider the role of a data analyst before committing to it. They reiterate the importance of understanding the realities of the job, including the need for self-learning, patience, communication, and realistic salary expectations. The speaker invites viewers to share their own insights and experiences in the comments and looks forward to future discussions on the topic.

Keywords

💡Data Analyst

A data analyst is a professional who collects, processes, and interprets data to help organizations make decisions. In the video's context, the role is discussed in terms of the skills and mindset required, such as self-learning and patience. The script emphasizes that while it's a good career path, it's not for everyone due to the need for continuous learning and problem-solving.

💡Self-learner

A self-learner is someone who can independently acquire knowledge and skills without formal instruction. The video script highlights the importance of being a self-learner in the data analyst role, as the field is constantly evolving and requires ongoing education, as illustrated by the speaker's own experience of learning SQL and Tableau without prior training.

💡SQL

SQL, or Structured Query Language, is a standard language for managing and manipulating relational databases. The script mentions SQL as one of the tools a data analyst might need to teach themselves, indicating the necessity for data analysts to be comfortable with database querying and management.

💡Data Visualization Tools

Data visualization tools, such as Tableau and Power BI mentioned in the script, are software applications used to represent data graphically. These tools help data analysts to create visual representations of data, making it easier to understand and communicate insights to stakeholders.

💡On-the-job Learning

On-the-job learning refers to the process of acquiring new skills and knowledge while working. The video emphasizes that data analysts must be prepared for significant on-the-job learning due to the unique setup of databases and tools in different companies, which requires adaptability and continuous self-education.

💡Impatience

Impatience is the tendency to seek immediate results or be unable to wait calmly for a process to unfold. The script cautions that data analysis can be a frustrating and patience-testing job due to debugging, locating data, and dealing with changing client demands, making patience a crucial trait for data analysts.

💡Communication

Communication in the context of the video refers to the exchange of information and ideas between data analysts and their team members, stakeholders, or clients. The speaker clarifies a common misconception that data analysts work in isolation, pointing out that they must maintain open lines of communication throughout projects.

💡Stakeholders

Stakeholders are individuals or groups who have an interest or concern in a project's outcome. In the video, stakeholders are mentioned as one of the parties that data analysts must interact with regularly, emphasizing the collaborative aspect of the role.

💡Salary Expectations

Salary expectations refer to the预先设想的 or anticipated income one might earn in a particular job role. The video script dispels the myth that data analysts start at high salaries, stating that the average range is between 60 to 80k, and that high-earning roles are typically reserved for more senior positions.

💡Debugging

Debugging is the process of identifying and fixing errors in code or data. The script describes debugging as a potentially frustrating aspect of data analysis, where patience is required to resolve issues and ensure the accuracy of analytical results.

💡Jira Tickets

Jira tickets refer to the tasks or issues tracked within Jira, a project management tool. The video mentions updating Jira tickets as part of a data analyst's routine, indicating the importance of keeping stakeholders informed about project progress and any issues that arise.

Highlights

Reality check on expectations of becoming a data analyst versus the actual experience.

Reasons why you should not become a data analyst, despite it being a good career path.

The first reason to avoid becoming a data analyst: not being a self-learner.

The need for self-learning in data analytics due to constantly changing tools and techniques.

The importance of independent learning, especially when lacking prior experience with SQL or data visualization tools like Tableau.

The significance of being able to find answers independently without relying on co-workers.

The role involves a lot of solo projects, requiring individual problem-solving skills.

The second reason to avoid the role: if you get easily frustrated or are impatient.

Challenges in the role include debugging code, locating data sources, and dealing with changing client requirements.

The third reason: if you do not like working with others, as the role involves constant communication.

The necessity of open communication with team members, stakeholders, and clients throughout projects.

Daily interactions include project updates, dealing with roadblocks, and updating Jira tickets.

The misconception that data analysts get rich quickly; typical entry-level salaries are between 60-80k.

Senior data analysts or above might make 90k+, but entry-level roles usually do not start at 100k.

Encouragement to research job listings and salary expectations before investing time and money into the field.

Transcripts

so today I want to have a reality check

on your expectations of becoming a data

analyst versus what it's actually like

being a data analyst So today we're

going to be talking about reasons why

you should not become a data analyst and

before we get into things I just wanted

to say that I am not trying to

discourage anyone from becoming a data

analyst I really think that it's a

really good career path to go down but

like with anything in any career path

it's not for everyone like you could not

pay me to do some other careers so

let's get into it

so the first reason that you should not

become a data analyst is if you're not a

self Learner in this role you really

have to learn a lot on your own so if

you're someone that may need a lot of

Hands-On help in order to complete a

task this may not be the best fit for

you things are constantly changing and

there's a ton of things that you have to

learn on your own in my situation I came

into this role with no prior experience

in data analytics so I had no I had no

training on SQL or how to use any of the

data visualization tools like Tableau

and click and I know a lot of people use

power bi I had no experience on using

any of those tools so for me I had to do

a lot of self learning on my own yes I

did get to do some like side by sides

and watch

um appear That's on my team as well as

watch my manager when he was doing some

of his projects but that wasn't what I

did all day every day in the beginning I

had to go out and pretty much Google

search a lot of different things I had

to learn how to do SQL on my own I had

to learn how to use Tableau pretty much

on my own so there's a and not to say

that's going to be the case for everyone

you guys may be like taking courses or

taking certifications so you're learning

in like kind of like a classroom setting

but that wasn't my experience and even

if you do learn those things in a

classroom type experience there's a lot

you're going to have to learn on the job

databases are going to be set up

differently the tools that your company

or these companies have are going to be

set up differently so there's going to

be a lot of on-the-job learning and you

can't really rely on tapping your

co-worker on the show on the shoulder

every time you need help with something

it's really something that you have to

be an independent learner and you have

to go out there and get the answers to

the information your first thought

should not be let me ask my co-worker

the answer to this and see if they're

going to figure it out or see if they

can help me out with this your first

first thought is really having to be let

me go in Search and try to find the

answer to this on my own because

everybody's busy in my role for the most

most part myself and my team we're doing

a lot of solo projects so they are

working on something completely

different than what I'm working on so

everyone is busy and has their own thing

going on and when you're asking someone

else for help with something you're

pretty much taking them away from the

project and the work that they have to

do that they have deadlines on so you

really have to have this mindset of

self-learning if you want to get into

the channel okay so I am editing this

video and I just want to add I'm not

saying that you can never ask your

co-worker for help I'm just saying that

that typically should not be your first

thought when you're needing help with

something or trying to find the answer

to something typically you want to try

and self-serve or find the answer on

your own before you reach out to another

now if it's something like they got the

data you need or of course reach out to

them like I hope that's kind of like

Common Sense common knowledge but yeah

if they there's going to be cases or

times where it's like this person I know

they have the information I know I need

to reach out to them definitely do that

but if it's like oh I'm trying to figure

out how to make this join work

Google it so the next thing is going to

be if you're someone who gets easily

frustrated or if you're impatient this

is a role you have to have a lot of

patience with patience with yourself

patients with these databases patients

with the tools because you're going to

run into issues in this job role you're

going to have problems with coding with

debugging with trying to find a freaking

data source sometimes like everybody's

trying to find out where the data is

there's like hundreds of tables and

Views that are out there and that can be

frustrating trying to locate data it can

be frustrating trying to debug your code

trying to figure out why things aren't

right it can also be frustrating working

with others when you're waiting on them

to provide you with information or

you're waiting on a client to sign off

on a project or you're dealing with a

client that is constantly changing their

mind on what they want and that can be

frustrating having to deal with someone

that doesn't know what they want and

you're having to kind of insert into

their project when they should be when

they should have that ready for you but

that's not how this works out all the

time so you may have to go through a lot

of trial and error working throughout

the project and your visualizations and

working with stakeholders and clients so

if you get easily frustrated or if

you're impatient this may not be the

best fit for you and tying into that the

next reason why you may not want to be a

data analyst is that if you don't like

to work with others I know for me when I

first got into this role I didn't think

that I would and this also ties into

communication you guys but when I first

got into this role I thought you know

like I always see people on their

computers typing with their headphones

on I didn't think that they interacted a

lot with others but you really do the

lines of communication have to be open

all the time throughout a project you

talk to people more than you think you

would and maybe more than you'd like to

you have to work with others you have to

work with people on your team you have

to work with your stakeholders or

clients you have to

update like we have like a 15 minute

daily scrum so I'm working with our

scrum Masters we're giving project

updates we're working through roadblocks

we're meeting with clients on status

updates on information we need things

that are happening we're having to

update our jira tickets on a daily basis

which keeps the client or stakeholder

updated on where we're at and then of

course they're commenting back on those

tickets for the most part to either give

you information or confirming where

you're at or possibly changing deadlines

you're going to be working with a lot of

people throughout your career as a data

analyst so if you're if you're not a fan

of talking to people if you're not a fan

of working with others this just may not

be the role for you so the next reason

why this may not be the best fit for you

is that you think that you're going to

get rich off becoming a data analyst I

feel like there's this common

misconception that when you get into

Data analysts like you take one of like

the data analytics certifications

you are going to get into an entry-level

role making a hundred thousand per year

now I have seen videos of people seeing

like they got their first data analyst

role making 100K But please understand

that is the exception that is not the

rule on average

data analyst roles are between 60 to 80k

like just go out on indeed go on

LinkedIn look at some of these job

postings I've seen some in my area that

are as low as 40K and when you look at

and read the job description what they

are really describing that they want is

a data scientist not a data analyst so

be mindful of that typically you'll

you're gonna see like a senior data

analyst or above making like 90k Plus or

even six figures on average that's not

typically the average of someone just

getting into data analytics so if you're

doing it thinking oh I'm going to take

the certification course and then I'm

going to start a job at 100k

please go look at job listings before

you wait like it to me before you waste

your money thinking that you're going to

take this course and then just go into a

100K job because that's typically not

the case average 60 to 80k range for a

data analyst which is still great money

and you can advance as you get into the

role longer you can make more money and

get into those higher ranges but

typically starting I just want to say

like that's not the norm that's the

exception that's not the that's not the

rule so I encourage you go out there

look at the job listings see what data

analysts or companies that you want to

work for or just local to your area are

making to see if that's something you

want to pursue before you invest your

time and your money into this I hope

that this information was helpful to you

if you're thinking about becoming a data

analyst just some things to consider if

you have some other points for anyone

looking to get into this role please go

ahead and drop account people out and I

will see you guys in my next video

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