Tom Mitchell
@TomMitchellData
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9-5: Building my one man data analytics agency @ 5-9: Helping busy professionals improve their data skills
Improve your data skills ➡️
Joined March 2023
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Wow Microsoft have free beginner courses in Data Science, Machine Learning and AI (all on Github).
Thats:
- 34 Weeks of Learning
- 70 Lessons
- 52 Quizzes
All for free?!
Thank you, Microsoft!
Here are the links:
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The standard Data Analyst roadmap is:
Excel
SQL
Visualisation Tool
Optional: Python/R
That's not very helpful.
Here's a detailed breakdown of what you need to learn for each:
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My career history:
2015 - Supermarket
2016 - Call Centre
2017 - Finance Analyst
2018 - Data Analyst
2021 - Senior Data Analyst
2023 - Data & Analytics Manager
Rome wasn't built in a day.
Keep grinding 💪
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Learn Data Analysis For Free in 2024:
1. Excel
2. SQL
3. PowerBI
Reports in PowerBI (Datacamp)
4. Tableau
5. Python
6. R
Make
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The difference between SQL, NoSQL, MySQL, and PostgreSQL explained in simple terms:
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RIP to old Data Analysis certificates.
Employers want certifications earned through exams.
Want to land a job quickly?
Here are the certifications that will help you do just that:
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When I'm hiring a data analyst, here's what SQL I'd expect candidates with 1-2 years of experience to know:
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How I would study Data Analytics if I had to start over:
Excel : Youtube + Microsoft Training Videos
SQL : Mode + SQLBolt
PowerBI: Youtube + Udemy Courses
Python : learnpython .org + Google Classes
Portfolio building - Youtube + Github Repos (Github Pages to host)
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I got rejected for a Senior Data Analyst role because I didn't know how to A/B test.
I wasn't going to let this stop me, so I taught myself.
Don't get caught out like me.
Here's my super-simple breakdown of how-to A/B test:
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Data cleaning is one of the most important skills for a data analyst.
Not Excel.
Not SQL.
Not PowerBI
Without clean data, any analysis done is unreliable.
Here's my data cleaning 101:
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Don't aim for this:
Excel - 100%
SQL - 0%
PowerBI/Tableau - 0%
Python/R - 0%
Aim for this:
Excel - 25%
SQL - 25%
PowerBI/Tableau - 25%
Python/R - 25%
You don't need to know everything straight away.
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Anyone with an Internet connection can learn Data Analysis for free:
Excel - Microsoft Training Videos
SQL - Mode
PowerBI - Udemy Course
Python - Google Classes
No more excuses.
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2K
Excel is a requirement for 99.9% of Data Analyst roles.
Don't waste time trying to learn everything it has to offer.
Prioritise these 5 things and leave the rest for later:
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2K
The standard data analyst roadmap is:
Excel
SQL
Visualisation Tool
Optional: Python/R
That's not very helpful.
Here's a detailed breakdown of what you need to learn for each:
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I've been a:
Data Analyst.
Senior Data Analyst.
Data & Analytics Manager.
Here are the three most important lessons I've learned at each level:
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I got my first data job because I knew SQL better than the other candidates.
There are 134 days left in 2023.
That means 134 opportunities to learn.
Here's my roadmap to master SQL by the end of the year🧵:
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Data cleaning is one of the most important skills for a Data Analyst.
Not Excel.
Not SQL.
Not PowerBI
Without clean data, any analysis done is unreliable.
Here's my Data Cleaning 101:
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449
2K
Don't aim for this:
Excel - 100%
SQL - 0%
PowerBI/Tableau - 0%
Python/R - 0%
Aim for this:
Excel - 25%
SQL - 25%
PowerBI/Tableau - 25%
Python/R - 25%
You don't need to know everything straight away.
16
329
2K
Data cleaning is one of the most important skills for a data analyst.
Not Excel.
Not SQL.
Not PowerBI
Without clean data, any analysis done is unreliable.
Here's my data cleaning 101:
13
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2K
Excel, SQL, Python & R play a huge part in data careers.
Don't spend $100's to learn them.
Here are 12 websites that will teach you for free: 🧵
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I've worked in data for more than 6 years.
It took me over 4 years to get my first job.
If I had to start again, I'd do things differently.
Here's how I would become a Data Analyst in 2023:
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1K
I got rejected for a Senior Data Analyst role because I didn't know how to A/B test.
I wasn't going to let this stop me, so I taught myself.
Don't get caught out like me.
Here's my super-simple breakdown of how-to A/B test:
20
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1K
SQL is the undisputed champion of the data world.
To be successful in data, SQL skills are a non-negotiable.
Want to become an SQL champion?
Here's a roadmap that will get you there:
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My career history:
2015 - Supermarket
2016 - Call Centre
2017 - Finance Analyst
2018 - Data Analyst
2021 - Senior Data Analyst
2023 - Data & Analytics Manager
Rome wasn't built in a day.
Keep grinding 💪
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168
1K
How to become a Data Analyst without a tech background:
34
345
1K
Learn data analysis for free in 2024:
1. Excel
2. SQL
3. PowerBI
Reports in PowerBI (Datacamp)
4. Tableau
5. Python
6. R
14
480
1K
Thinking like a Data Analyst didn’t come easily for me.
I'd spend hours staring at datasets, unsure what questions to ask.
I knew I had to change if I wanted to have a successful career in data.
Luckily, I found a way through.
Here's what I did in 4 steps:
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1K
RIP to old Data Analysis certificates.
Employers want certifications earned through exams.
Want to land a job quickly?
Here are the certifications that will help you do just that:
11
334
1K
It took me 2 years to go from Data Analyst to Senior Data Analyst.
I could've done it faster with what I know now.
Here's what I'd do differently if I was starting again as a Data Analyst:
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Anyone with an Internet connection can learn Data Analysis for free:
Excel - Microsoft Training Videos
SQL - Mode
PowerBI - Udemy Course
Python - Google Classes
No more excuses.
14
504
1K
Don't aim for this:
Excel - 100%
SQL - 0%
PowerBI/Tableau - 0%
Python/R - 0%
Aim for this:
Excel - 25%
SQL - 25%
PowerBI/Tableau - 25%
Python/R - 25%
You don't need to know everything straight away.
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306
1K
Data Interviews 101
In the past 6 years, I've interviewed countless people for data-related roles.
Want to know a secret?
I use the same 5 questions every time:
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How to write a killer data analyst resume with no experience:
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It took me 4 years of studying to get my first data analyst job.
As a beginner with no experience, the journey to employment can seem daunting.
I want you to do it quicker than me.
I've condensed everything you need to do into 6 steps:
🧵
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I've been a:
Data Analyst.
Senior Data Analyst.
Data & Analytics Manager.
Here are the three most important lessons I've learned at each level:
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Nobody showed me how to create a data analysis portfolio.
I was lucky to land my first job.
To become a data analyst in 2024, it's non-negotiable.
Here's how you can do it in 5 steps:
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Excel is a requirement for 99.9% of Data Analyst roles.
Don't waste time trying to learn everything it has to offer.
Prioritise these 5 things and leave the rest for later:
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I have a PDF with 3 Data Analyst resume templates which helped my mentees land $60-70k jobs
I usually charge for them
But, I'm loving interacting with you guys
So i'm giving it away for free
All you have to do is comment 👍 and i'll dm the download link (must be following) ⬇️
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Data Analyst vs Data Scientist
What's the difference?
You need to know this if you want to work in data:
🧵
(Disclaimer - this is based on my experience)
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Want to land a Data Analyst job in 2024?
Here's what you need:
- Excel
- SQL
- PowerBI or Tableau
- Python or R
and master:
- Communicating data
- Problem solving
- Data transformation & cleaning
- Data visualisation theory
Make 2024 your best year yet.
I'm rooting for you.
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A 4-year Data Science degree from Harvard costs $330,000+
Want to learn about Data Science but don't want to spend that much?
Here are 6 Data Science courses from Harvard that cost $0:
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Data Analysis is not:
- Writing SQL code
- Building PowerBI Dashboards
- Creating Pivot Tables in Excel
- Using Python to wrangle data
It's:
- Listening for problems
- Selecting the right tool to solve the problem
- Overcoming challenges
- Helping drive action and following up
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A breakdown of:
- Data Analysts
- Data Scientists
- Data Engineers
- Business Analysts
And the skills needed for each role 🧵:
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Learning SQL changed my life, and it will change yours too.
Do yourself a favour and make 2024 the year you master it.
To help, here's my 2024 SQL roadmap:🧵
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When starting out, a lot of people struggle with SQL Joins.
The truth is, once you've grasped it, you won't forget it.
Here's my super simple breakdown of common SQL joins:
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If you want to learn Python for Data Analysis:
Don't try and learn everything it on offer.
Instead, focus on:
Pandas (cleaning, transforming, and analysing)
NumPy (for math)
Matplotlib (for data visualisation)
That'll get you up and running.
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I combined 3114 CSV files with 4 lines of Python code:
Here's how:
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As a Data Analyst its crucial to know the difference between a Dashboard and Report
Here's my super simple breakdown:
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Data Analysts are in high demand, but the competition is tough.
Here's a dead-simple guide to landing your first Data Analyst role:
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How to optimise your LinkedIn profile to land high paying data jobs:
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Data analysis is not:
- Excel
- SQL
- Python/R
- PowerBI or Tableau
Data analysis is your ability to spot patterns in data and transform raw data into actionable insights.
The tools help you get there, they don't do the job for you.
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Most people think new Data Analysts need to use many tools.
The truth is, you only need 3.
Don't waste your time with tools you won't use on the job.
Here are the only 3 you need to get started:
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A Data Analyst who understands customer segmentation will never be short of work.
Problem is, it's not covered often in courses.
So, I've put everything I know about it into this thread.
Grab a pen and some paper and get stuck in 🧵:
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Data Analysis is not:
Building Dashboards 25%
SQL 25%
Plotting data 25%
Cleaning data 25%
It's:
Communication/Meetings 50%
Understanding the data 20%
Data cleaning & transformation 15%
Analysing data 5%
Validating/Tweaking 10%
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Data Analyst vs Business Analyst
What's the difference?
You need to know this if you want to work in data:
🧵
(Disclaimer - this is based on my experience)
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Over the last 2 years I have reviewed 100's of Data Analysis portfolios.
99% sucked.
For the 1% that were outstanding, here's 5 things they had in common:
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Pandas (Python) methods worth knowing for Data Analysis:
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926
If you want to learn Python for Data Analysis:
Don't try and learn everything it on offer.
Instead, focus on:
Pandas (cleaning, transforming, and analysing)
NumPy (For Maths)
Matplotlib (For Data Visualisation)
That'll get you up and running.
17
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926
Without Data Engineers, there would be no data science, analysis or BI
That's why it's one of the highest-paying data roles with average salaries of ~$150k
Knowing where to start can feel overwhelming
Don't worry, here are 3 Data Engineering certifications that make it simple:
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How I would study data analytics if I had to start over:
Excel : Youtube + Microsoft Training Videos
SQL : Mode + SQLBolt
PowerBI: YouTube + Udemy Courses
Python : learnpython .org + Google Classes
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Matplotlib (Python) Cheatsheet for Data Visualisation:
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I've been working in data for over 6 years.
I've been writing SQL since day one.
Here are the most common keywords I use:
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SQL is the bread and butter of Data Analysis.
For any Data Analyst, it's non-negotiable.
Use these case studies to test your skills with real-world problems:🧵
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You have 6 seconds to make your data analyst resume stand out when you apply for a job.
How do you do that?
By showcasing your skills through projects.
Here are 6 portfolio projects (with datasets) guaranteed to WOW employers. 👇
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SQL Query Execution Order:
FROM: Tables are joined.
WHERE: The data is filtered.
GROUP BY: The filtered data is grouped.
HAVING:The grouped data is filtered.
SELECT:The final data is returned.
ORDER BY: The final data is sorted.
LIMIT: Returned data is limited to row count.
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How to write a killer data analyst resume with no experience:
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What's more powerful than:
Excel?
SQL?
Python?
Having the ability to use them together.
Excel can import data from SQL using Power Query.
Create SQL tables from Excel files.
Python can read/write Excel Files/CSVs.
Python can access data in SQL tables.
Go beyond the basics.
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Here's the fastest way to use Python if you already know SQL:
8
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A Data Analyst who understands customer segmentation will never be short of work.
Problem is, it's not covered often in courses.
So, I've put everything I know about it into this thread.
Grab a pen and some paper and get stuck in 🧵:
13
238
875
Data analysis is not:
- Excel
- SQL
- Python/R
- PowerBI or Tableau
Data analysis is your ability to spot patterns in data and transform raw data into actionable insights.
The tools help you get there, they don't do the job for you.
11
214
848
As a Data Analyst its crucial to know the difference between a Dashboard and Report
Here's my super simple breakdown:
4
201
854
How I went from Entry Level Analyst to Senior Data Analyst in 2 years:
13
131
847
If you want to learn Python for Data Analysis prioritise:
- NumPy (maths)
- Pandas (data wrangling)
- Matplotlib (Data viz)
- Seaborn (built on top of matplot lib, has higher level interface capabilities)
- OS (Operating System Interaction for working with files and folders)
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How much Excel, SQL and PowerBI did I actually use as a data analyst? (Honest take):
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How to become a Data Analyst without a tech background:
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Becoming a Data Analyst doesn't need to be more complicated than:
1. Excel/Stats
2. SQL
3. Tableau/ PowerBI ➡️Build dashboards
4. Python/R ➡️ Analyse + Visualise Data
5. Using the above, build Portfolio projects (From data cleaning → Tell the story → Recommendation & Actions)
6
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812
Thinking like a Data Analyst didn’t come easily for me.
I'd spend hours staring at datasets, unsure what questions to ask.
I knew I had to change if I wanted to have a successful career in data.
Luckily, I found a way through.
Here's what I did in 4 steps:
11
191
823
The standard Data Analyst roadmap is:
Excel
SQL
Visualisation Tool
Optional: Python/R
That's not very helpful.
Here's a detailed breakdown of what you need to learn for each:
14
170
760
If you want to learn SQL for Data Analysis prioritise:
- Data Types
- SELECT Statements
- Filtering/Sorting
- JOINs
- Aggregation Functions
- Subqueries
- Window Functions (Analytic Functions)
If you want more help learning, here's my best SQL threads and free resources:
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The tools I used as a Data Analyst:
- SQL
- Python
- PowerBI
- Cloud tech (Azure/AWS)
The tool I use the most? Excel.
Here's why I recommend you learn Excel in 2023:
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When I first started as a Data Analyst I was dashboard crazy.
But, I learnt quickly that not validating my work properly pre-deployment would seriously damage my reputation.
Don't make the same mistake I did.
Here's a 4-step framework I used to bulletproof my work:
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8 Data Analysis terms you should know:
Cleanse - fix or remove.
Analyse - examine patterns.
Visualise - create visuals.
Transform - modify structure.
Correlate - identify relationships.
Predict - forecast trends.
Interpret - explain results.
Extract - retrieve information.
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Data Analysis projects from YouTube won't get you a job.
Following tutorials won't get hiring managers attention.
Thinking outside the box will.
Here's my 5-step process for creating unique projects that demand attention🧵:
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It took me 2+ years to become a successful Data Analyst.
I really struggled at first.
I learned so much by asking the right questions.
If I was starting my data career again, here are 5 questions I'd ask everyone I met:
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I went from entry-level analyst to manager of 20 in 4 years.
I climbed the ladder by knowing exactly what I needed to do at every level.
It's not always clear what you need to do to move up.
Here's my breakdown of each role from Analyst to Manager:
(Based on my experience)
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If you want to learn Python for Data Analysis:
Don't try and learn everything it on offer.
Instead, focus on:
Pandas (cleaning, transforming, and analysing)
NumPy (for math)
Matplotlib (for data visualisation)
That'll get you up and running.
11
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732
Learn Data Analytics whilst working full time:
Find 60 minutes per day to learn the absolute basics (Excel, SQL, PowerBI/Tableau) on Youtube.
Do this for 2-3 weeks.
Write down project ideas as you learn.
Start building projects.
Don't wait to "feel ready" just go.
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GitHub offers the best free Data Science education on the internet.
But there are more than 372 million repositories to choose from.
How do you find the best ones?
Bookmark these 5 repositories and start learning fast:
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Anyone with an Internet connection can learn Data Analysis for free:
Excel - Microsoft Training Videos
SQL - Mode
PowerBI - Udemy Course
Python - Google Classes
No more excuses.
5
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765
I moved from writing SQL code for a company with 4 million customers to one with 26 million.
The first day I wrote some basic SQL and my query crashed.
I found out the hard way working with data of this size needs serious consideration.
Here's what had to change and why:
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Data Science and Python are a match made in heaven.
But there are over 137,000 Python libraries to choose from.
Here are 8 you will use the most as a Data Scientist:
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6 analysis techniques I used the most as a Data Analyst:
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