Description
SQL is one of the in-demand programming languages that you can learn. In this PostgreSQL tutorial, I will be explaining the use of vanilla SQL but also combining it with the use of a relational database management system. Yes, you guessed it: I will be using PostgreSQL.
Since many specialists are choosing to make data-driven decisions instead of those based on intuition and a bare-bones prediction, learning SQL for data analysis is becoming increasingly popular. SQL is no longer regarded as a language for programmers, but also for data analysts, marketing specialists, and basically anyone who deals with data.
This course teaches SQL for beginners: from the creation of a database and the use of various statements to insert, import, update, or select data.
Principles of SQL and PostgreSQL
In this PostgreSQL tutorial, I will be starting from the SQL fundamentals (its installation as one of the examples). After reviewing several case studies about an analytics professional, I turn to the fundamental SQL statements that you use to manage your database. The CREATE statement is the basic function of creating a database.
The definition of SQL is as follows: it is the standard language for managing data stored in relational database management systems. If you want a description that would be SQL for beginners, this language is for storing, manipulating, and retrieving data.
PostgreSQL (or Postgres) is a free relational database management system that uses SQL and adds new features to improve data management. In this PostgreSQL tutorial, you will learn about the extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types, and functions.
Why SQL for data analysis?
I have already mentioned that SQL is the language for data analysts, but you might not be convinced just yet. It is true that software developers use SQL, but many people outside of the programming scope are learning SQL as well. Here are the main reasons why SQL fundamentals are relevant to business managers and analysts:
- SQL for data analysis is perfect due to its relatively lower learning curve. It means that it is easy to learn even without experience with other programming languages.
- SQL helps you manage huge amounts of data. Additionally, there are options for organizing data for different purposes.
- The decision-making process is becoming more data-based. Therefore, it is essential to find a cost-effective way to handle information. SQL is perfect in this aspect as well as its statements help you get insights from data.
What will you find in this course?
This PostgreSQL tutorial aims to teach beginners everything they need to know about SQL and the use of relational database management systems. Do not miss a chance to improve the way you are handling information. While spreadsheets in Excel are the traditional way of storing and handling information, give SQL a shot to take data management to the next level. Since I will be explaining all statements and main concepts, you do not need to have any prior experience to learn from this PostgreSQL tutorial!
What Will You Learn?
- All the essential SQL commands
- How to use SQL tools like GROUP BY, JOINS and subqueries
- Sorting and filtering commands in SQL
- About the most popular string of SQL, mathematical and date-time functions
- How to enhance the performance of your database by using Views and Indexes
Requirements
- No prior knowledge is necessary
Curriculum
Course consist of total 7h 23min of content, in total.
Section 1: Introduction
Section 2: Case Study : Demo
Section 3: Fundamental SQL statements
Section 4: Restore and Back-up
Section 5: Selection commands: Filtering
Section 6: Selection commands: Ordering
Section 7: Alias
Section 8: Aggregate Commands
Section 9: Group By Commands
Section 10: Conditional Statement
Section 11: JOINS
Section 12: Subqueries
Section 13: Views and Indexes
Section 14: String Functions
Section 15: Mathematical Functions
Section 16: Date-Time Functions
Section 17: PATTERN (STRING) MATCHING
Section 18: Data Type conversion functions
Section 19: User Access Control Functions
Section 20: Bonus Section: Nail that Interview!
Section 21: Performance tuning tips
Section 22: Bonus Section : Database Basics
About the Instructor
Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics, and Python.
Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.
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