Beginner's Guide to Data & Data Analytics, by SF Data School (Udemy.com)
The Data Analytics Context We Wish We Had, When We First Started: Concepts, Tools, Roles, Processes, and Terms Explained
Created by: Colby Schrauth
Last updated August 2024
Our take
Based on the ratings of 26,862 students, a sample of their written reviews and the syllabus, as the course stood in August 2024. No course pays to be reviewed.
This is a short orientation, not a skills course. Colby Schrauth of the San Francisco Data School explains what data analytics, data science and data engineering are, how the common tools fit together, how data moves through a pipeline, and what to learn next. It runs about 92 minutes across nine lectures, and a written handbook comes with it. The description is upfront that it is not an Excel or SQL tutorial, and there are no quizzes or exercises.
Reviewers praise the clear explanations and the everyday examples. One called it well paced, with good real world examples for people who aren't computer savvy. The complaints are consistent too. Some found it too basic or already familiar, and one wanted a pretest so they could skip what they knew. Two said the delivery was hard to follow, one citing speed and one a monotone voice, and the second also missed any interaction to keep them focused. Of 26,862 ratings, about half are five stars and under 2 percent are one or two.
With 71,473 students, it is a popular first stop, and the 4.5 rating holds up. The last update was August 2024, which matters little for concepts. If you need the vocabulary and the lay of the land before choosing a path, 90 minutes is a fair trade. If you already work around data, or hoped to build something, pick a hands-on course instead.
Pros
- Explains data analyst, scientist and engineer roles in plain language, per reviewers
- Short enough to finish in an evening: nine lectures, about 92 minutes
- Free written handbook backs up the videos for quick review
- Ends with a learning roadmap and career paths so the next step is clear
Cons
- No quizzes, exercises or projects, so nothing is practiced
- Some reviewers found the content too basic or already familiar
- A few found the delivery fast or monotone and hard to stay focused on
well paced, good real word examples for non computer savvy people
Truly for absolute beginners. No requirements, and it is explicitly not an Excel or SQL tutorial.
What you will learn
- Free access to our Data Fundamentals Handbook, which compliments the video content in this course in written form
- The world of data is massive, but that doesn't mean it has to be complicated. Cut through the noise and get a clear vision of the "Big Picture"
- Learn the distinguishing factors between Data Analytics, Data Science, and Data Engineering
- Discover data tools – which are the most popular, how they work together, and why some are preferred over others
- Demystify how data moves from collection to analysis, and what people, processes and technologies are involved
- Get a step-by-step learning roadmap to becoming a practitioner of Data Analytics, and insight in to career paths that are most relevant
- Context gives each of us the grounding we need to think about data more meaningfully and know it better. Learn to break down some of data's most prized concepts and terms
Course content
9 sections · 9 lectures · 1.5 hours of video 1 article
- 1Setting the Stage: An Introduction to Data 1 free preview1 lecture · 12 min
- 2Roles and Skills of Data Professionals 1 free preview1 lecture · 18 min
- 3Classification of Data Analytics Tools1 lecture · 10 min
- 4Deep Dive: The Data Analytics "Tool Triangle"1 lecture · 14 min
- 5Data Types, Files, and Formats1 lecture · 12 min
- 6Data Pipelines: How Data Moves From Collection to Analysis1 lecture · 10 min
- 7Data Flashcards: Key Concepts and Terminology1 lecture · 8 min
- 8Data Analytics Learning Roadmap and Career Paths1 lecture · 8 min
- 9Thank You1 lecture
Who it is for
The instructor says it suits
- People who want to learn more about data, but don't know where to start
- Anyone who believes that learning to work with data will change the way they do business, live their lives and help others
- Someone who wants to ultimately work with data tools and learn how to make data-driven decisions
- This course is the first step in learning how to work with data, building the context needed to understand the big picture
- This course is NOT an Excel or SQL tutorial
What you need before you start
- No requirements or experience necessary, just an interest to learn more about the world of data
How it compares
Against the other 371 rated Udemy courses in Data Analysis on CourseDuck:
- Rating4.5 out of 5higher than 49% of them
- Reviews26,862#8 of 372 by number of reviews
- Length1.5 hoursshorter than 89% of them
- Last updatedAugust 2024earlier than 63% of them
Course Description
The inspiration for building this course is right in the title – it's the Analytics Context We Wish We Had, When We First Started.
This course now includes free access to our Data Fundamentals Handbook, which compliments all the video content in this course in written form.
This course starts with an introduction to the world of data. Context is critical, and it most definitely applies to learning how to work with data. Before even touching a data tool, amongst many other things, we believe it's vital that one fully understands the context surrounding data.
From there you'll delve deep in to the differences between Data Analytics, Data Science, and Data Engineering, and how each of these roles provide value in their own way. In addition, you'll gather a deep understanding of the tools used by professionals – which are the most popular, when one would be preferred over another, and how they can be used in collaboration.
Next, you'll learn about the technical processes that encompass the lineage of data. This section will enable you to internalize the concept of a Data Pipeline, and start building-up a lexicon and literacy for how data moves from collection to analysis.
Finally, you'll see a step-by-step learning roadmap to become a practitioner of Data Analytics. In this section you'll gain access to recommended steps to take after this course, and career paths that are most relevant.
One of the biggest challenges in getting started with data is finding the right place to start, we believe this is it. You are 90 minutes away from truly understanding the world of data – a perspective we've built over a decade of experience.
Instructor Details
- 4.5 Rating
26,862 Reviews
Colby Schrauth
Co-Founder of The San Francisco Data School, and Analytics Team Lead at Square. Previously, a Lead Instructor for Data Analytics at General Assembly San Francisco, and an Instructional Associate for Columbia University’s MS in Applied Analytics.
The world of data is incredibly massive. For anyone looking to start their journey in a data profession, it can quickly become an overwhelming endeavor. No one knows this better than Colby Schrauth.
Colby took a non-linear path to becoming a data professional. His educational background is Finance, but he’s spent the majority of his professional career in Business Development roles – selling payroll to small businesses for ADP, helping large enterprises understand the value of online communities with Lithium Technologies, and more. However, the goal of becoming a practitioner of data persisted throughout these experiences.
Along the path to becoming a data professional, Colby was constantly battling internal thoughts of discouragement:
• I don’t have a Computer Science background, will I ever be taken seriously?
• What data tools should I learn, and how do I get started?
• The data ecosystem is complicated and evolving quickly, will I be able to keep up?
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Reviews
By Jennifer Smith on 7/1/2026
Information technology has transformed so rapidly (even before AI) that I have been spinning my wheels. Where does one start? How does one deal with terminology let alone harness the benefits? The creators of this course, equally overwhelmed by it, worked through it all for themselves. One of their products is this excellent class. This does not require you to learn to write computer programs. Rather, you learn what the most frequently used programs are and how to employ them in ways relevant to your needs. The course developers break down information on data storage and formatting (ex, Excel). Then they instruct students about programs that process the data formats into usable results (charts, graphs, etc). Until I participated in a recent work project, I had no clue about the interoperability of Excel with other software. This class is exactly what I needed to learn how data storage and processing function. I highly recommend it.
By Alex Cannon on 6/15/2026
I have to take it for work. I understand that some people may not understand the concepts but this is fairly universal knowledge.. I am sure things will pick up but at the moment, I wish I could have pretested and then covered the parts I do not know.
By Nelisa Mqhedlana on 4/22/2026
A helpful, well-presented introductory course in Data Analytics that helped me get a better grasp of roles working with data. It helped clarify different roles and gave insight into expectations of a beginner data analyst position.
By Khululekani Mgezi on 3/29/2026
Taking this Data course has been very useful. As a Finance Manager at SALGA Free State, it helps me analyze financial data more effectively, spot trends, and make better decisions. The course is a good match for me because it strengthens my data skills and supports my work in budgeting and financial planning.
By Michael Pecoraro on 3/24/2026
This was a great course. The instructors made the topics engaging, easy to follow and understand. This course provides a good foundation from which to build from. I highly recommend this course and any others taught by these instructors!
By Mmakoko Mothapo on 3/23/2026
The course structure was well-organized, starting from fundamental principles and gradually progressing to more advanced topics, which made it easy to follow even without a strong prior background.
By Vicki Jackson on 3/19/2026
Honestly, I don't see why it was mandated for me, but the information was very well presented. The speakers were engaging and using real world examples was always helpful. Even though it's a video you can rewind and replay, the pacing was good and I didn't have to keep rewinding because I missed something that went too fast or didn't hold my attention.
By Sharon G Weber on 3/18/2026
It was mostly a review of different types of data and uses of data that I was already aware of. It gave me a big picture of data sources, uses and career paths. It was worth my time to take the class.
By Amit Mistry on 3/13/2026
Excellent overview and framework, especially for people who use and work with data and want to understand the broader context and map out a roadmap to go deeper and further in their capabilities.
By Charles W. Mayo on 3/10/2026
At this point it is moving fairly quickly and not all information presented so far is sticking. Hopefully with additional instruction and scenarios the information will become more clear.
By Anjan Banerjee on 12/27/2020
Amazing course
By Garima Agrawal on 12/27/2020
Nice introductory course on learning ways to modulate data into information......
Quality Score
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Overall Score : 90 / 100






