Learn Data Analysis with Free Lessons & Tips

Data Science seeks to discover new and unique questions that can drive business innovation. In contrast, Data Analysis aims to find solutions to these questions and determine how they can be implemented within an organization to foster data-driven innovation. Read: Career in data science and its Scope

1. Theory:
Use Coursera and EdX for theory, concepts, and applications of probability, statistics, linear algebra, calculus, and machine learning.

2. Data Visualisation:
Tableau and PowerBI are easy-to-use tools with GUI facilities for data visualization and business intelligence. Matplotlib in Python and ggplot in R are good packages for visualization.

3. Programming:
Python and R are great free tools that you can download from the internet. RStudio for R and Anaconda for Python are two good tools to write and test codes. You can use Datacamp for learning and hands-on practice of Python and R. Then practice machine learning algorithms using Python or R.

4. Big Data:
For Big Data, AWS or Azure can be used for storage and Spark can be used for processing. You need to pull the data from the database, process or filter the data and bring it to a usable format. For getting and processing data SQL is a very good tool. You can use the dplyr package in R or pandas in Python for data processing tasks.

Dear Learner,
First, we've to understand the tool's capabilities. As you've mentioned Tableau and Power Bi. These are mainly known for data visualisation and not for Data Analytics. And Quick View is not a good option for Data Analytics as there are many compromises and also not in high demand in the market.
I would instead suggest you go for some reliable Analytical tools like SAS, R.
Hope it helps!

Skills - Python and libraries (Seaborn, Pandas, Numpy etc), Statistics, SQL, R(better to have), tools like SAS , Tableau, Knowledge of database concepts

How to learn ?

step 1 - Learn Python(plenty tutorials on Youtube)

step 2 - Learn pandas, matplotlib,seaborn,numpy etc. libraries of python

step 3 - Learn concepts of statistics

step 4 -  Start practicing on datasets available on internet

step 5 - Go to a trainer for SAS/Tableau