SQL-DA.AJ2
SQL for Data Analytics
Learn how to effectively use SQL for optimal data preparation, performance, and analysis.
- Practice in 17 Laboratorios prácticos — nothing to install
- 10 Lecciones interactivas y 66 topics mapped to the official exam objectives
- 180 Preguntas del examen de práctica
Beginner A tu propio ritmo · 1 año de acceso
17 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
10Lecciones interactivas
66Topics
17Laboratorio en vivo
180Preguntas del examen de práctica
33Tarjetas didácticas
33Glosario de términos
01 / Habilidades que obtendrás
What you will be able to do
Try Free →
No se requiere tarjeta de crédito
This SQL for Data Analytics course assists you in navigating through the data pools confidently. You’ll learn to prepare, clean, and analyze data effectively, turning raw information into valuable insights. By brushing up your skills in aggregate functions, window functions, and data preparation techniques, you’ll be well-equipped to tackle real-world data challenges.
- Analyze data effectively using SQL
- Prepare and clean datasets to ensure accurate and reliable information
- Utilize aggregate functions to summarize and draw insights from large datasets
- Apply window functions for advanced analytical queries and comparisons
- Transform raw data into structured formats for better interpretation
- Improve performance and efficiency in data retrieval by optimizing SQL queries
- Implement best practices for working with relational databases and ensuring data integrity
- Explore complex data types, including JSON and arrays, for comprehensive analysis
- Visualize data using SQL to support informed decision making
Course Highlights
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10 Lecciones estructuradas Cobertura completa de los objetivos principales del curso
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17 LiveLabs prácticos Escenarios interactivos guiados con evaluación instantánea
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180 Preguntas de práctica Pruebas de evaluación con justificaciones de respuesta detalladas
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1 año de acceso completo Aprendizaje a tu propio ritmo, accesible en cualquier momento y en todos los dispositivos
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
10 Lecciones interactivas · 66 topics01 Preface 11 topics +
- About the Course
- Audience
- About the Lessons
- Conventions
- Setting up Your Environment
- Installing Git
- Loading the Sample Datasets – Windows
- Loading the Sample Datasets – Linux
- Loading the Sample Datasets – macOS
- Running SQL files
- Accessing the Code Files
02 Understanding and Describing Data 7 topics · 2 Laboratorio en vivo +
- Introduction
- Data Analytics and Statistics
- Types of Statistics
- Working with Missing Data
- Statistical Significance Testing
- SQL and Analytics
- Summary
2 Laboratorio en vivo in this lesson — see the labs panel →
03 The Basics of SQL for Analytics 11 topics · 2 Laboratorio en vivo +
- Introduction
- The World of Data
- Relational Databases and SQL
- PostgreSQL Relational Database Management System (RDBMS)
- Creating Tables
- Basic Data Types of SQL
- Data Structures: JSON and Arrays
- Column Constraints
- Updating Tables
- SQL and Analytics
- Summary
2 Laboratorio en vivo in this lesson — see the labs panel →
04 SQL for Data Preparation 5 topics · 2 Laboratorio en vivo +
- Introduction
- Assembling Data
- Cleaning Data
- Transforming Data
- Summary
2 Laboratorio en vivo in this lesson — see the labs panel →
05 Aggregate Functions for Data Analysis 6 topics · 1 Laboratorio en vivo +
- Introduction
- Aggregate Functions
- Aggregate Functions with the GROUP BY Clause
- Aggregate Functions with the HAVING Clause
- Using Aggregates to Clean Data and Examine Data Quality
- Summary
1 Laboratorio en vivo in this lesson — see the labs panel →
06 Window Functions for Data Analysis 5 topics · 1 Laboratorio en vivo +
- Introduction
- Window Functions
- Statistics with Window Functions
- Window Frame
- Summary
1 Laboratorio en vivo in this lesson — see the labs panel →
07 Importing and Exporting Data 5 topics · 1 Laboratorio en vivo +
- Introduction
- The COPY Command
- Using Python with your Database
- Going Passwordless
- Summary
1 Laboratorio en vivo in this lesson — see the labs panel →
08 Analytics Using Complex Data Types 7 topics · 2 Laboratorio en vivo +
- Introduction
- Date and Time Data types for Analysis
- Performing Geospatial Analysis in PostgreSQL
- Using Array Data types in PostgreSQL
- Using JSON Data types in PostgreSQL
- Text Analytics Using PostgreSQL
- Summary
2 Laboratorio en vivo in this lesson — see the labs panel →
09 Performant SQL 6 topics · 3 Laboratorio en vivo +
- Introduction
- The Importance of Highly Efficient SQL
- Database Scanning Methods
- Killing Queries
- Functions and Triggers
- Summary
3 Laboratorio en vivo in this lesson — see the labs panel →
10 Using SQL to Uncover the Truth: A Case Study 3 topics · 3 Laboratorio en vivo +
- Introduction
- Case Study
- Summary
3 Laboratorio en vivo in this lesson — see the labs panel →
Laboratorios prácticos Our edge
17 Laboratorio en vivos- Creating a Histogram in Excel
- Exploring Dealership Sales Data
- Running the SELECT Query
- Creating and Modifying Tables
- Generating a List Using the UNION Query
- Building a Sales Model
- Analyzing Sales Data Using Aggregate Functions
- Analyzing Sales Using Window Frames and Window Functions
- Reading, Visualizing, and Saving Data in Python
- Performing Text Analytics
- Searching and Analyzing Sales
- Implementing Hash Indexes
- Creating Functions with Arguments
- Creating a Trigger to Track Average Purchases
- Using SQL Techniques to Collect Preliminary Data
- Analyzing the Difference in the Sales Price Hypothesis
- Analyzing the Performance of the Email Marketing Campaign
Los laboratorios se ejecutan en tu navegador; no hay nada que instalar.
03 / Preguntas frecuentes
Preguntas antes de empezar
How is SQL used in data analytics? +
SQL (Structured Query Language) is used in data analytics to query, manipulate, and manage data stored in relational databases. It allows analysts to retrieve specific data, perform calculations, and generate reports, making it essential for extracting insights and making data-driven decisions.
Which SQL is better for data analysis? +
The choice of SQL largely depends on the specific use case and the database system in use. PostgreSQL is often favored for its advanced features and compliance with SQL standards.
Is SQL harder than Python? +
SQL is considered easier to learn than Python due to its simpler, declarative syntax.
Do I need prior SQL knowledge to take this course? +
No, you don’t need prior SQL knowledge to take this course. It is designed for beginners and professionals alike, starting with the basics and gradually progressing to more advanced topics.
What are the benefits of learning SQL for data analytics? +
Learning SQL for data analytics allows you to work with large datasets, perform data preparation, clean and transform data, and run complex queries to extract meaningful information. SQL is a critical skill for anyone working with data, helping you to make data-driven decisions, improve business intelligence, and improve overall analytical capabilities.
Is SQL in Data Analytics a useful and high-paying skill?+
Yes, SQL is a precious skill in the job market. It is crucial for roles like data analyst, data engineer, and business intelligence analyst. Once you’ve refined your skills, you can reach for high-paying job opportunities, especially in data-centric fields.
Learn SQL for Data Analysis
Gain practical skills in SQL and transform and analyze data to achieve success in a data-driven world.
- 1 año de acceso completo
- 17 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito