Popular Articles

Snowflake Data Mart – How to Build One?

June 26th, 2024 By Skand Agrawal in Data Warehousing, Snowflake

Your organization may store large volumes of data in a single Snowflake data warehouse. However, extracting data specific to individual departments from the data warehouse can be time-consuming, delaying your…

Apache Airflow Use Cases and 5 Best Practices

April 23rd, 2025 By Arsalan Mohammed in Data Strategy

Apache Airflow is a tool that can create, organize, and monitor workflows. It is open-source hence it is free and has a wide range of support as well. It is…

Mastering Snowflake Replication: A Comprehensive Guide to its Capabilities

June 7th, 2024 By Sarthak Bhardwaj in Data Warehousing, Snowflake

With large volumes of data generated daily, it might be challenging for you to store and manage the data efficiently. Database replication can solve this problem by creating and storing…

Snowflake TO_DATE: Level-Up your Data Transformation

June 7th, 2024 By Satyam Agrawal in Data Warehousing, Snowflake

Date and time are important data types for analyzing trends and patterns during data analysis. They also help manage deadlines and inventories by comparing changes in resources over a period…

AWS Aurora vs Snowflake: 5 Critical Differences

May 10th, 2024 By Manisha Jena in AWS, Data Strategy, Versus

Nowadays, with ever-increasing data, storage and analysis of large volumes of data have become basic foundations of any organization. While focusing on storage and analysis, which two concepts come to…

5 Best Cloud Data Warehouses (Based on G2 Ratings)

August 30th, 2024 By Suraj Poddar in BigQuery, Data Warehousing, Redshift, Snowflake

In today’s cloud-rich landscape, businesses are turning to data warehouses to store, manage, and analyze their data. As of 2024, over 65k companies use cloud data warehouses to enhance their…

Redshift Dynamic SQL: Explained Step-by-Step

May 10th, 2024 By Skand Agrawal in Data Warehousing, Redshift

Companies use Data Warehouses to store and analyze their business data to make data-driven business decisions. Querying through huge volumes of data and reach to a specific piece of data…

Enhance Data Integrity With Snowflake Date Format

June 7th, 2024 By Sarad Mohanan in Data Warehousing, Snowflake

Data and time information are essential for accurately capturing, organizing, and processing data for effective data management. These functions help you extract information from the storage system in a logical…

Fivetran vs. Matillion: Who Wins As The Right Data Integration Tool?

April 23rd, 2025 By Arun Chaudhary in Platform, Product

Data silos, messy formats, poor data quality, and information stuck in different systems can make it hard for your organization to get a clear view of what’s really going on.…

Data Warehouse vs Data Lake vs Data Lakehouse – Key Comparisons

July 23rd, 2024 By Gabriela Aleksandrova in Data Engineering

With the vast amount of data being collected today for various purposes, there is an increasing need to find the proper data storage, which also heavily depends on your specific…

What Is Enterprise Data Integration?

February 2nd, 2024 By Catherine Schwartz in Data Integration

As businesses integrate and adapt to modern technologies and processes, data used increases and is kept in different platforms—whether you keep them on on-site physical servers, cloud servers, or hybrid…

Understanding Conceptual vs Logical vs Physical Data Models for Effective Databases

November 11th, 2024 By Khawaja Abdul Ahad in Data Engineering

Consider designing a skyscraper. You would first need to create a high-level design. Next, you would create detailed plans for each floor. Lastly, you would choose the building materials and…

What Is AWS Data Pipeline: Core Concepts & Implementation Explained

April 5th, 2024 By Vivek Sinha in AWS, Data Strategy

AWS Data Pipeline is a web service that lets you process and moves data at regular intervals between AWS computing and storage services, as well as on-premises data sources. It…

Snowflake Warehouse vs Database: Deep Understanding

June 26th, 2024 By Sarthak Bhardwaj in Data Warehousing, Snowflake

Many organizations often ponder if Snowflake, a modern data analytics platform, is a data warehouse or database. Data warehouse and database are two key components of Snowflake’s architecture. Both play…

Snowflake Testing for Data Warehouses Simplified 101

May 17th, 2024 By Dimple M K in Data Warehousing, Snowflake

A Data Warehouse has become the need of the hour today because most companies are shifting to data-driven solutions. Businesses use multiple online tools and services to reach out to…

Snowflake Current Date: Efficient Date-Based Function

June 7th, 2024 By Anaswara Ramachandran in Data Warehousing, Snowflake

Date and time functions are crucial when extracting information from large datasets. Imagine a situation where you have to make marketing decisions based on seasonal trends and product performance. You…

HubSpot to Snowflake Integration: 2 Easy Methods

May 17th, 2024 By Nathaniel Oliver in Data Integration, Snowflake

Unlock the full potential of your Hubspot data by integrating it seamlessly with Snowflake. With Hevo’s automated pipeline, get data flowing effortlessly. Watch our 1-minute demo below to see it…

How to Implement Snowflake dbt Integration Step by Step

May 31st, 2024 By Dimple M K in Data Integration, Snowflake

The exponential data growth has increased the demand for tools that make data processes, such as data collection, integration, and transformation, as smooth as possible. These tools and technologies can…

Google BigQuery vs Athena: 7 Critical Differences

May 10th, 2024 By Nitin Birajdar in BigQuery, Data Warehousing, Versus

Today, every organization is moving to serverless cloud offerings to solve many data-related challenges. The primary issue these companies face occurs while trying to manage vast data repositories. In such…

How to Code a Data Pipeline Python

September 11th, 2024 By Raju Mandal in Data Engineering, Data Pipeline

A Data Pipeline is an indispensable part of a data engineering workflow. It enables the extraction, transformation, and storage of data across disparate data sources and ensures that the right…