SQL for Data Science
During the training, you will learn how to write queries to retrieve data from the database using SQL, filter it, change its format, use multiple sources as a single source, and perform other operations on the database in a very simple and practical way. This will help you carry out calculations on data and optimize the process of preparing daily, weekly, and monthly reports and analyses. The training is designed in a way that even those with no prior programming experience will easily understand.
Training table
SQL for Data Analytics
SQL for Data Analytics
SQL für Datenanalyse
SQL для анализа данных
Information about the training
In most enterprises, programs like Excel are used to perform operations on large volumes of data, which often takes considerable time and sometimes the program simply lacks the power to execute these operations. The purpose of this course is to ensure that these time-consuming processes are carried out more efficiently and in less time using SQL, which is more suitable for this type of work. By the end of the training, you will acquire the skills to prepare reports, display necessary data, retrieve data from the database, add, delete, and edit records using SQL. This training will help participants alter the outcomes of complex business reports, manage data to finalize reports, and build new data models simultaneously.
Who is this training for?
Business Managers, Business Analysts, Data Analysts, those learning Data Analytics and anyone interested in this field, individuals seeking answers to complex business issues and preparing reports, business owners, sales or marketing professionals wanting to better understand their company, anyone working with data tables or databases, those wanting to learn the fundamentals of Big Data and data analytics, organizations using Microsoft's database, professionals working in marketing, finance, accounting, operations, sales, manufacturing, healthcare, finance, or any other industry, anyone preparing reports from large datasets, and anyone looking to build a career in data science.
Certificate
Individuals who successfully complete the training will be awarded the Certified SQL for Data Analytics certificate, while others will receive a participation certificate. You can see a sample certificate on the right.
Learn SQL in 4 hours!
SQL for Data Analytics Tutorial
Luke Barousse
Learn how to efficiently retrieve, filter, and format data, combine multiple data sources, and perform crucial operations on your database in under 4 hours with this comprehensive video tutorial. Designed for beginners and professionals alike. Video Courtesy: Luke Barousse
Syllabus
Session 1
- What is Data? What is a Relational Database?
- What is SQL and why should we learn it?
- SQL Data Types
- SQL Operations (DDL, DML, DCL, TCL)
- Selecting and Filtering Data from the Database (SELECT, FROM, WHERE, TOP, DISTINCT, =, <>, LIKE, BETWEEN, AND, OR, ORDER BY)
Case Study 1
Filtering Data in the "Human Resources" Database.
Session 2
- Understanding NULL and Handling NULLs
- Data Type Conversion
- Comparison Functions
- Using Single Row Functions (Substr, Nvl, Length, Decode, Case, etc.)
- Mathematical Operations and Functions (Sum, Count, Average, etc.)
- Applying Group By and Having
Case Study 2
Aggregating and Sorting Data in a Real Business Database.
Session 3
- Retrieving Data from Multiple Tables Simultaneously, JOIN Operator (JOIN, LEFT JOIN, RIGHT JOIN, CROSS JOIN, FULL JOIN)
- Set Operators - Combining the Results of Different Queries into a Single Result
- Subqueries - Using Nested Select Queries
Case Study 3
Joining Tables in the "Human Resources" Database.
Session 4
- Constraints in SQL and Their Application
- DDL (Data Definition Language) and DML (Data Manipulation Language) Operations
- Introduction to Analytical Functions (lead, lag, etc.) and Their Usage.
Case Study 4
Data Analysis and Retrieval in a Financial Database.
Trainers
Bahruz Gasimov
EXPERT FOR DATA QUALITY AND ASSURANCE MANAGEMENT, PASHA BANKOur professional trainer Bahruz Gasimov currently works as an “Expert in Data Quality and Assurance Management” at Pasha Bank. He has also worked in the data field at companies such as TuranBank OJSC, Yapı Kredi Bank Azerbaijan, and Unibank, and has over 14 years of professional work experience.