The goal of this post is simple: to guide you into doing data analytics like a genuine pro.
That means (beside the very first resource), this list is not meant for beginners. This is a guide to truly advanced analytics from the very best — and in some cases, challenging — online authorities.
Even better, this is a list of free resources that, if applied, could make 2016 the best year of your data science and marketing life.
1. Google Analytics Academy
By: Google
Content Format(s):
- Written
- Video (Short and Long)
- Pretests for Certification
Who It’s For: Everyone (Period)
What It’s About:
Google’s Analytics Academy offers the only official curriculum — along with a host of detailed pretests and supplemental presentations — to guide you into becoming a Google Analytics Certified Partner.
The Academy is divided into five courses:
- Google Tag Manager Fundamentals
- Mobile App Analytics Fundamentals
- Ecommerce Analytics: From Data to Decisions
- Google Analytics Platform Principles
- Digital Analytics Fundamentals
Its comprehensive approach means that even if you won’t be pursuing Certified Partner status, you can easily begin by digging directly into the area that’s most applicable to your business.
Each of the five courses is broken down into a series of Units that contains relatively short (10-15 minute) video lessons, two or more “Further Reading” articles from experts, and an “Activity” for self-assessment.
The best feature, however, is that each course also contains a series of Live Event Videos that are much longer than the video lessons and are hosted by the best of the best in the world of online analytics.
2. Building Your Marketing Funnel with Google Analytics
By: Moz
Content Format: Written
Who It’s For: Marketers and Ecommerce Owners
What It’s About:
Building Your Marketing Funnel with Google Analytics is essentially a single, in-depth post by John Doherty of HireGun. HireGun is a platform that “matches companies seeking a consultant or agency with the right agency for their needs.”
The article, as John says, “walk[s] you through how to identify the [online] channels that are performing best.” In other words, it lays out a data-driven process for building on your marketing funnel’s existing strengths, while keeping an eye on its weakness.
John begins by explaining how crucial understanding the path your customers actually take when buying truly is. Then he dives into the article’s main subject: building a marketing funnel based on Google Analytics data. Even more helpful, he clearly defines the key differences between a “Digital Marketing Funnel” and traditional sales funnels.
The post is divided into the following well-outlined and integrated sections:
- What is a funnel?
- Identify channels based on funnel level.
- Applying the data.
- Excel sheet.
- Example and conclusion.
What sets this post apart is how convenient it is.
It’s long enough to give you the full guidance you need to create your own online marketing funnel but at the same time short enough for you to go through it over and over, confirming and comparing everything you’re currently doing with what you should be doing.
Both John’s outline and language are straight to the point. You won’t get confused or spend too much time trying to connect the dots. All you have to do is follow the guide.
And the icing on the cake: it includes examples and bonus spreadsheets which you can download for your own use for free.
3. 21 Real-World Examples Of Concatenating Marketing Data In Excel
Content Format: Written
Who It’s For: Marketers
What It’s About:
This is a blog post on the Annielytics blog owned and run by Annie Cushing who – in her own words – aims to “help you put your data in stilettos and make it work the pole.”
In this short but insightful post, Annie walks you through the data concatenation process (or “stitching together”) using Excel in two ways: (1) the concatenation function and (2) the concatenation operator.
She explains each option in detail, lets you in on her favorite, and tells you in concrete terms when and why she uses it.
After taking you through the two methods, Annie then gives twenty-one real-world examples that come both from outside marketers as well as from herself.
What stands out is how clearly she explains her methodologies while maintaining a lighthearted and humorous tone.
4.Data Analysis & Statistical Inference
By: Duke University (Coursera)
Content Format:
- Short Videos (5 to 10 minutes).
- Assignments
- Pretests and a Final Exam for Certification
Who It’s For: Statisticians and Data Scientists
What It’s About:
Duke University offers ten full weeks of study via Coursera in this comprehensive analytics course.
According to the University, one of the main goals of this course is to help you “interpret results correctly, effectively, and in context without relying on statistical jargon.”
The course syllabus is divided into 10 units:
- Introduction to Data.
- Probability and Distributions.
- Foundations for Inference.
- Finish Up Unit 3 + Midterm.
- Inference for Numerical Variables.
- Inference for Categorical Variables.
- Introduction to Linear Regression.
- Multiple Linear Regression.
- Review/Catch-Up Week.
- Final Exam.
Each unit is further divided into three to four subsections, which makes it easy to consume by digesting a small portion at a time.
As with all the resources on this list, the course itself is also free. That’s a huge plus, considering all you stand to gain. In addition, most of the associated resources are free too.
Lastly, to keep you on track and ensure you absorb everything, Duke offers interactive quizzes and assignments throughout.
5. Advanced Data Structures
By: MIT
Content Format:
- Written
- Lecture Videos (1.5 hours each)
- Assignments
- Final Project for Assessment
Who It’s For: Marketers and Data Scientists
What It’s About:
This is a graduate level course which was taught at MIT in the Spring of 2012. According to the description, “This course covers major results and current directions of research in data structure.”
The course covers the following major areas:
- Time Travel.
- Geometry.
- Dynamic Optimality.
- Memory Hierarchy.
- Hashing.
- Integers.
- Dynamic Graphs.
- Strings.
- Succinct.
That’s a tall order, but MIT provides a detailed calendar covering 22 topics each with a detailed description, student notes, professor’s notes, and lecture videos that you can download to view offline. As per the calendar, each of the two weekly sessions, which you can digest on your own timeline, takes 1.5 hours. There is also an optional “open-problem session” per week which takes about 2 hours.
As you’d expect, there is a vast amount of material to use for this course. Even better, almost every resource for this course is downloadable. Thus, you don’t have to be online every time you want to access the materials.
Better and better …
When you look at this list again, you realize that it’s really not a matter of selecting one or the other. These are resources you can learn from one-by-one in chronological order or use to address the areas most applicable to you business.
Thankfully, you can pick and choose without worrying about time and without worrying about paying.
Do you have a favorite free resource for truly advanced analytics and data experts.
Please share it in the comments.
