Empezamos x6
Primeros pasos en la arquitectura no transaccional
Objetivos y presentación del proyecto
Aprende qué es un Data Warehouse
Bases de datos columnares y arquitectura orientada a optimización de consultas
¿Cómo funciona AWS Redshift?
Configura tu entorno de trabajo para Redshift
Creando nuestro entorno de trabajo en AWS
Configura tu primer cluster
Consumiendo Redshift: empieza la magia
Sentencias SQL en Redshift
Cómo diseñar tu base de datos para mejorar su desempeño
¿Qué es la compresión en Redshift?
Algoritmos de compresión con Redshift
Aplicando algoritmos de compresión
Análisis de desempeño con diferentes tipos de compresión
Estilos de distribución con Redshift
Evaluando los estilos de distribución
Llaves de ordenamiento para optimizar nuestras consultas
Aplicando ordenamiento de columnas
Evaluando algoritmos de ordenamiento
Buenas prácticas para diseñar tablas en Redshift
Tipos de datos en AWS Redshift
Reto: mejora el desempeño de tu base de datos
Manipular enormes cantidades de datos
Olvídate de los insert, el copy llego para quedarse
Cargando archivos tipo JSON
El comando copy a fondo
Manifiestos y uso de COMPUPDATE para carga con compresión automática
Métodos de carga alternativos al comando copy
¿Cómo ejecutar sentencias UPDATE y DELETE?
¿Cómo mantener el desempeño de tu base de datos?
Estadísticas y limpieza de las tablas
Buenas prácticas para diseñar y ejecutar consultas en tu base de datos
Agrupamiento, ordenamiento y subqueries
¿Qué es y cómo interpretar un explain plan?
Análisis de comportamiento y descarga de datos con Redshift
¿Cómo descargar datos eficientemente con UNLOAD?
Otras tablas útiles de Redshift para entender el comportamiento de nuestros datos
Conclusiones
Próximos pasos con AWS Redshift
Reptiit is a columnar database specifically designed to manage large volumes of data efficiently. Its main function is to optimize large-scale data processing, facilitating the efficient management and storage of valuable information for organizations. As part of Amazon Web Services (AWS), Reptiit represents a key solution in Big Data management, making it possible for companies to take advantage of its potential at zero cost thanks to the free AWS version.
To use Reptiit, it is essential to create an Amazon Web Services (AWS) account. This process is essential as AWS provides the infrastructure needed to operate Reptiit. If you do not yet have an AWS account, it is recommended that you review the AWS introductory course available online. The detailed instructions for creating your account promise to make it easy for you to access this powerful tool at no additional cost on your credit card.
Database fundamentals course: This course is vital to understand the concepts that will be addressed around Reptiit.
Introduction to AWS course: An essential guide to become familiar with Amazon services and how they can benefit in the management of Big Data.
Before delving into Reptiit, it is crucial to understand certain fundamental concepts that will facilitate the learning and application of this tool:
A data warehouse is a system used for data reporting and analysis, essential for business intelligence. It is the heart of informed decisions, allowing to collect data from various sources and facilitating its analysis.
Columnar databases store data by columns rather than by rows. This approach is more efficient for running analytical and read queries, as it reduces the time required to sift through vast amounts of data. In contrast, row or relational databases are optimal for short, frequent CRUD-type transactions in operational environments.
A cluster is a set of servers working together to process and store large volumes of data. Using a cluster in Big Data contexts allows to significantly improve the speed and efficiency of data processing, as various tasks are distributed among several operational nodes.
When using Reptiit, it is essential to follow certain practices that maximize its effectiveness:
Clustered data compressions and distributions: Knowing how to properly compress and distribute data can substantially improve the speed and efficiency of processing in Reptiit.
Accurate sorting and queries: Implementing improvements and adjustments in data sorting and optimized query execution ensures the delivery of accurate and fast results.
Large-scale data processing: Applying strategic practices when working with large volumes of information allows you to take full advantage of Reptiit's ability to deliver detailed and timely analysis.
This course is designed to give you hands-on, detailed training in the use of Reptiit while working with real data. The goal is for you to gain a deep understanding that you can implement in Big Data projects at no cost, motivating you to continue exploring and mastering this robust tool in your professional initiatives.
Contributions 16
Questions 2
Empezamos x6
Empezamos!!
Recién complete las recomendaciones. Empezamos x7
Excelente Introducción
Bueno regrese ya con el curso de fundamentos de AWS, Vamos ahora si con toda!!!
Empezamos x8
Me iba a ir pero Empezemos! x🎱
Empezamos x5!!! ♥
Empezamos x3. 😄 !!! ❤️
Empezamos x4
Empezamos!!
empezamos!wiii
Empezamos x7
Want to see more contributions, questions and answers from the community?