Data Analytics Resources
Updated: Oct 4
Below are the best resources I've found related to data analytics whether it's learning new skills, hosting a portfolio, or get inspiration from creators. I will update these resources periodically as I find new resources and include my commentary as well. If there's anything you think I should add or would like to let me know of a resource you found helpful email me at: email@example.com.
Table of Contents:
The following resources include everything technical about learning data analytics. From course platforms and specific courses to where you can practice your coding skills or host your portfolio.
Websites where you can find specific courses on tools like SQL or Python. Some platforms go into more detail about the soft skills and how to break into tech as well.
Coursera - has many courses on a variety of topics, it has popular courses for data analytics like the Google Course or the IBM course. Along with specific courses for skills. There's a free option and a subscription based option which is $59/month.
Maven Analytics - they have everything from specific courses to learn skills to a Bootcamp and learning paths for different types of careers. Check out the "Learn" tab on their site for specifics. It is a subscription based service for $39/month.
freeCodeCamp - basic introduction to various skills and it's completely free
Udemy - has all types of courses that if you get them on sale they cost usually ($15-$25). I used this for learning specific skills like SQL or Python.
Datacamp - an all encompassing platform to learn common skills in data analytics. They have specific courses to "learning tracks" for jobs like Data Analyst or Data Scientist. The platform has a free version (first chapter of every course and select courses) and a paid version which is $25/month.
Codeacademy - this is tailored towards people interested in coding. It has a variety of coding languages but it does include courses on Python and SQL. There's a free version and a paid version which is subscription based. The pro version is $25/month.
Below are some specific courses I've taken and have personally used.
Data Analyst Bootcamp (Free) from Alex the Analyst - this is a Youtube playlist with over 50 videos. He walks you through the basics of SQL, Excel, Tableau, Power BI, Python, and more. Along with projects and a way to create a portfolio website for free. Highly recommended if you have a limited budget and want to get started learning right away.
Google Data Analytics Course - overview of what data analysis is and what a data analyst does along with introducing important skills needed for a data analyst like Excel, SQL, Tableau and R (check out my review of the course). In short it's good as an introduction but it won't get you job ready alone.
Data with Danny Serious SQL Course - focuses on case studies to provide real world practice, it takes a while to set up the IDE but worth it for the case studies.
The Complete Python Bootcamp From Zero to Hero in Python - walks you through Python you learn the basics to more complicated ideas like object oriented programming. It also has assessments and mini-projects to complete to test your knowledge which I found the most useful.
Python for Data Science and Machine Learning Bootcamp - learn how to use common Python libraries used in data analytics/science like NumPy and Pandas. I'm still going through this program but have learned from this instructor before and would recommend him.
The Complete SQL Bootcamp: Go from Zero to Hero - learn PostgreSQL to perform data analysis. The setup takes a bit but once you do it you can analyze a dataset using SQL. It includes real world problems and a database.
These sites are where you can practice your skills. Kind of like practice problems you would do during math classes. Most of these are free but may have a paid version. Some focus on interview questions that may be asked during technical interviews.
DataLemur - SQL, interview questions asked by top tech companies
W3Schools SQL Practice Problems - list of exercises to practice SQL
stratascratch - 1,000+ real interview questions from favorite companies, SQL and Python
hackerrank - gamify practicing coding skills (Python, SQL)
leetcode - with over 2,000 questions to practice coding skills
Portfolio Hosting Platforms
Below are a few sites where you can host your data analytics portfolio that don't require coding knowledge. Which one you choose depends on what skill/s you want to focus on showcasing.
Github - great for hosting coding files like SQL or Python, it's free. You can also create your own website/landing page
Maven Analytics - An all-in-one platform for hosting a data analytics portfolio. I haven't personally used it but I've heard great things about it.
Tableau Public - you can host your Tableau dashboards/visualizations on this site for free
Carrd.co - an easy way to create a landing page for your portfolio. It's free and you can link to your projects that may be hosted on different sites
novyPro - useful for hosting your PowerBI dashboards/visualizations
Sites to Find Datasets
Below are sites I've found free and public datasets.
Datahub - This site covers a wide range of topics from climate change to entertainment, but it mainly focuses on economic and business data.
Dataset Search - You're able to use Google to search for datasets. It's great if you have a particular topic in mind.
Kaggle - It has variety of free datasets provided by users from everything to arts & entertainment to social science data.
Data Gov - Public data from the US government from everything from crime to healthcare.
Maven Analytics Data Playground - Datasets that are hand picked by Maven's instructors. These datasets can be more fun like analyzing the Harry Potter movies scripts to more business focused like analyzing sales of a pizza place.
Awesome Public Datasets - A list of topic focused public data sources that are high quality. These are collected from blogs, answers, and user responses.
Datacamp Datasets - These datasets are from a variety of fields from real estate to retail. All of the datasets have the data and packages needed.
NASA Data - Has open-data provided to the public from NASA. The dataset pages only hold the metadata and the actual data may be on another NASA site. There will be links to the data in these other locations.
These are other resources where you can learn more about data analytics. Specifically the soft skill side and learning how to break into the field.
Tina Huang - she's a data scientist but she talks about how to learn specific data science skills, studying tips and general career advice
Luke Barousse - portfolio projects, how to get a data job
Below I've linked to some of my favorite LinkedIn creators and generally the topics they write about along with anything else I found useful from them.
Danny Ma - SQL, data science, and data analytics
Avery Smith - founder of Data Career Jumpstart Bootcamp talks about all topics in data, specifically how to get a data analyst job
Albert Bellamy - content creation, marketing analytics, career pivoting
Vin Vashishta - data science, machine learning, and career advice
Christian Wanser - data science, data analytics, data
Annie Nelson - data careers, data analytics, and her How to Break into Tech as a Data Professional Guide
Megan Lieu - careers, data analytics, SQL tips, work-life balance and what it's like working for a start-up
Chris French - a teacher turned data analyst who talks about his process to becoming a data analyst
Jess Ramos - data analytics, tech careers, and other relatable content about what it's like being in the tech field
Lauren Rosenthal - education in tech, data analytics, personal development
Amna Ahmed - career change, data analytics, business intelligence
Data Career Podcast - How to transition into the data analytics field or getting a job with no prior experience
SuperDataScience Podcast - Latest in data science and interviews with top data scientists
Data Bytes - Bite-sized data stories, professional interviews, and trends in the world of data.
Data Ideas Podcast - Conversations with other data professionals about use-cases for data and analytics.
Data Skeptic - A critical look at topics related to data science, statistics, machine learning and more.
Data Driven - Brings experts from the fields of data, software engineering, machine learning and AI.
Analytics Power Hour - Experienced hosts share their thoughts and experience on a wide range of topics.
Data & Impact - Explores different perspectives about analytics from a wide range of industry experts.
Women in Data Science Worldwide - Leading women in data science share their advice, work, and lessons from their lives.
Career Foundry (Data Analytics Blog) - Career Foundry is an online school for career change into tech. it has courses and programs for data analytics. I specifically like looking at their data analytics blog for articles on data topics like SQL and general career advice.
freeCodeCamp news - I mentioned it in the course platform section but it also has articles on coding skills. While it's mostly about coding (less about data analytics) it's still a useful resource in case you want to expand your technical knowledge
Towards Data Science on Medium - if you have a Medium subscription ($50/year or $5/month) this is a great resource for learning anything related to data science including concepts, ideas and codes. If you don't pay you are limited to only 3 articles a month on Medium.
the muse (Data Analytics Career page) - a free website with plenty of blog posts on finding jobs, how to build an effective resume, and more. This specific page focuses on careers in data analytics/science.
Below are some of my favorite email newsletters. These are focused on data science or data analytics.
The Automated - discover the latest trends and tools in AI, it has links to articles and trending tools
Data Dad - it's designed for aspiring data analytics, going over topics like skill building, networking and motivation
The Query - a newsletter for the data professional for staying informed, improving skills, and advancing their careers with a bit of humor
The Data Career - thoughts and advice for current and aspiring data professionals that you can read in 3 minutes or less