I found Anlytics is present everywhere in systems I work. That lead me to think deep about the whole topic. I am taking the opportunity to do a focused learning about Analytics.
The goals are:
- High level concepts of Analytics
- Types of Analytics and their usage
- Techniques
- Tools - Identify some basic tools and methods you could learn
- Web-based Analytics - Google, Adobe, etc.
- Revisit how Analytics is used in your workplace
- Introduction to Analytics | Analytics for Beginners Course (Part 1)
- Descriptive, Predictive, and Prescriptive Analytics Explained
- 3 Must Know Analytical Concepts For Every Professional / Fresher in Analytics
- The Data Scientist’s Toolbox | Coursera: Do week 3 and 4
- Displaying and comparing quantitative data | Khan Academy
- Tutorial: Basic Statistics in Python — Descriptive Statistics – Dataquest
- A Complete Tutorial to Learn Data Science with Python from Scratch
- Quick Guide to Build a Recommendation Engine in Python
- Powerful Guide to learn Random Forest in R and Python
- Different Types of Analytics | Analytics for Beginners Course (Part 2)
- Big Data Basics - What is Big Data Analytics? | Sisense
- Data Mining Basics - What is Data Mining? | Sisense
- Business Analytics 101 | Business Analytics 3.0
- Jigsaw Academy
- Analytics for Beginners
- Supply Chain Management & Business Intelligence Articles | Halo
- https://www.edx.org/course/subject/data-analysis-statistics - Interesting list of courses
- No More Excuses: 10 Best Ways to Learn Analytics Online | Sisense
You can classify Analytics based on quite a few basis. One of the most popular approach is based on what they do:
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
Descriptive Analytics looks at past data and determines what happened. It usually doesn't identify why something happened. You will need to augment other types of analytics to get the full benefit of your data.
Example: An online store may find that it has 20% less users visiting its website (which is a not good sign). That's Descriptive Analytics.
Diagnostic Analytics tries to find out why something happened.
Example: Following the example, we found out that the website became much slower in last month, which probably explains why there were less traffic.
Predictive Analytics attempts to predict the future based on what happened in the past.
Prescriptive Analytics attempts to prescribe a solution to influence future outcomes. It's difficult as it sounds. Common methods uses - Machine Learning, Business Rules and Algorithms.
- Reports vs Dashboards
- Reports are static in nature, and usually scoped to specific business area.
- Dashboards are interactive, and allows you to slice/dice on the fly. They have been available to senior management usually, but the norm is breaking now.
- Read here.
- TBD: The Basics Of Data Analytics – K2 Data Science & Engineering
I am following this: How to Use Google Analytics [The Absolute Beginner's Guide] - Moz
TODO: Write up