Overview: What is dbt and what can it do for your data pipeline? One tool that we recommend and often use is dbt (data build tool), which focuses on simplifying and accelerating the process of data transformation. In this blog,…
Short answer ✅ Organizing data so that it becomes understandable to work with. Long Answer ⏩ All software applications that rely on data have a data model. Depending on the goal the application serves, it needs a specific type. When people…
Introduction In today’s data-driven world, businesses are constantly seeking ways to leverage the power of data for insights and decision-making. One popular approach is building a dashboard, a visual representation of key metrics and data points that provides a quick…
Data Build Tool (dbt) is a command line tool that helps data analysts and engineers transform, analyze, and visualize data in their warehouse. It is designed to work with popular warehouses such as Snowflake, Redshift, and BigQuery, and integrates with…
In today’s data-driven world, having a robust and efficient data management system is crucial for any organization looking to gain valuable insights from their data. One such system that has been gaining traction in recent years is Snowflake, a cloud-based…
Most businesses today are data-driven, and to make sound decisions, they need access to accurate and timely data. However, setting up and maintaining a data warehouse can be costly and time-consuming. Apache Superset is an open-source tool that makes it…
Building a data warehouse can be a costly endeavor, with several factors impacting the final price tag. Factors such as the size and complexity of the data, the tools and technologies used, the number of users, and the level of…
In today’s data-driven world, companies are constantly on the lookout for new and innovative ways to extract value from the vast amounts of data they generate and collect. To meet this demand, there are three key approaches that have emerged…
When it comes to designing a data warehouse, there are two main schema models that are commonly used: the star schema and the snowflake schema. Both of these models have their own unique characteristics and benefits, but they also have…
Introduction Data integration and data warehouses are two essential components of modern data management and analysis. They enable organizations to combine data from multiple sources, clean and transform it, and store it in a centralized repository for easy access and…