How to load data from Salesforce to Redshift: A definitive guide
In this guide, you will learn about various methods to transfer your data from Salesforce to Redshift.
In this guide, you will learn about various methods to transfer your data from Salesforce to Redshift.
Is your data warehouse modern enough? Learn the differences, benefits and available tools and strategies for easy migration.
Data warehousing is the process of collating data from multiple sources in an organization and store it in one place for further analysis, reporting and business decision making. Typically, organizations will have a transactional database that contains information on all day to day activities. Organizations will also have other data sources – third party or internal operations related. Data from all these sources are collated and stored in a data warehouse through an ELT or ETL process.
A data warehouse is a centralized storage system for structured data. The data stored here is used for reporting, analytical processing and business intelligence.
Our newest benchmark compares price, performance and differentiated features for Redshift, Snowflake, BigQuery, Databricks and Synapse.
The data lakehouse is a promising new technology that combines aspects of data warehouses and data lakes.
When setting up a modern data stack, data warehouse modeling is often the very first step. It is important to create an architecture that supports the data models that you wish to build. I often see people going straight to writing complex transformations before thinking about how they want to organize the databases, schemas, and tables within their warehouse. To succeed, it is key to design your data warehouse with your models in mind before starting the modeling process.