Learn SQL with following tutorial on W3Schools. This tutorial allows you to learn basics of SQL and test yourself without actually installing a Database. Highly recommended for Beginners 

https://www.w3schools.com/sql/default.asp

Practice till you can clear this quiz also hosted on W3Schools: https://www.w3schools.com/sql/sql_quiz.asp

Recommended Video

Learn how to use Excel for data modeling. This will help take your excel knowledge to next level. 

This post will include list of mySQL databases that you can restore for practicing your data analysis skills.

Please click link to download dataset:  Books Data

Please check this article for some suggestions on how to use this dataset

Please check the following article for instructions on how to restore a dataset from backup

Restoring mySQL backup

Data visualization techniques vary a lot based on types of target users who will be consuming data. 

Join this "Storytelling with Data" community and practice your skills in improving your ability to use data to tell stories. This community is setup on following principles

• Practice in a safe environment
• Take regular challenges and exercises
• Get Feedback from others

SWD Community

Recommended Article for data analysts learning Python and SQL

Full article written by Sanjana is posted here 

A data analyst or data scientist get lots of opportunity to work on Python and SQL. Python with its enormous library support provides data analyst with a magic wand to manipulate and visualize data. Likewise SQL helps us store millions of records and establish relationships with other tables for optimal data management. There are scenarios that require a Python program to directly load data into a back-end database. For example, if a data frame is dynamically modified periodically or at random instances, uploading the csv file for each data update into the database is not feasible. In this post, we will go through how to integrate a Python program with MySQL database.

While basic data analytics can be done by using data in CSV or Excel files but most common data analytics in organizations will require querying data from databases.

As beginner gaining database skills will help you hit the ground running. Following step by step tutorial can teach you skills to understand database concepts.

SQL Tutorial on W3 Schools

Installing mySQL

We will be providing datasets that you can setup in mySQL database and practice your skills

Data visualization comes in so many varieties that it is sometimes hard to pick the right way to present information to stakeholders. As a technologist it is very easy to assume stakeholders require a very sophisticated visualization and build lot of features into one dashboard.

This also happens because visualization tools made it very easy to provide lot of interactivity. At the same time, each interactivity enables a "feature" in dashboard and supports more use cases. This can result in feature bloat and confuse users more than necessary.

Building a static visualization will meet requirements of not very savvy stakeholders and give them the insight they need.

We have learned some tips and tricks by watching how Statista uses data visualization for data journalism. This can be applied in business context also to increase awareness and align business stakeholders of state of business.

We will cover some sample data analysis use cases with examples on this site in coming weeks to demonstrate variety of examples to illustrate how visualization can be tailored to address different needs.

We launched a data visualization competition in August 2020 in partnership with datamentors.in.  We are announcing winner who used Python libraries to create all visualizations as per the competition. We will provide winning submission here soon.

Becoming a data analyst requires learning data visualization techniques that will be required for variety of business users

Learning these skills requires datasets that are easy to understand before building nice dashboards for business users

If you are finding it difficult to find simple datasets that will help you learn these skills, you can find sample datasets on this site or build your own similar to this. Modify these datasets so that can relate to it

1. Personal Expenses: We all try to analyze how we are spending our money. Looking at data by expense category and time is always important for better financial planning.
2. Professional experience: We can articulate our professional experience if we can quantify our experience: Number of projects, average duration etc.

Please click download Datasets below (Registration required to download datasets)