Data Warehousing

Understanding Airflow BigQuery Operators: 4 Critical Aspects

September 20th, 2021 By Karan Singh Pokhariya in BigQuery, Data Warehousing

This article introduces you to Google BigQuery and Airflow BigQuery Operators. It also provides a comprehensive guide for a better understanding. This article makes it easy for you to understand…

Understanding Amazon Redshift Regex: Simplified 101

September 17th, 2021 By Vishal Agrawal in Data Warehousing, Redshift

Companies stores terabytes of data from multiple data sources into Data Warehouses and Data Lakes. The data exists in different formats and is not ready for analysis. Data Cleaning becomes…

Snowflake JDBC: How to Connect to Snowflake Using the JDBC Driver

September 17th, 2021 By Nicholas Samuel in Data Warehousing, Snowflake

A few years back, building a Data Warehouse was an expensive process that required the use of specially designed hardware appliances in your Data Center.  However, the invention of Snowflake…

Google BigQuery SQL : Syntax & Usage Simplified

September 17th, 2021 By Ayush Poddar in BigQuery, Data Warehousing

Explore the Google BigQuery SQL syntax, functions, and key benefits of utilizing it in further sections. Let’s get started. One of the popular Cloud-based Data Warehouses is Google BigQuery which…

BigQuery Timestamp Functions: Syntax & Example Queries Simplified 101

September 15th, 2021 By Manisha Jena in BigQuery, Data Warehousing

Data Warehousing architectures have rapidly changed over the years, and most of the notable service providers are now Cloud-based. Therefore, companies are increasingly moving to align with such offerings on…

BigQuery Date Functions 101: Key Syntax and Usage Simplified

September 14th, 2021 By Rakesh Tiwari in BigQuery, Data Warehousing

In today’s world organizations are constantly looking for data-driven insights. However, it can be difficult to Extract, Store, and Analyze that data as it rapidly grows in scale and scope.…

Understanding Amazon Redshift Window Functions: Made Easy 101

September 14th, 2021 By Ofem Eteng in Data Warehousing, Redshift

There is a surge in data generation by organizations, and this growth has been exponential, therefore, giving rise to technologies and pathways in which this data could be harnessed for…

BigQuery String Functions 101: Syntax and Usage Simplified

September 13th, 2021 By Rakesh Tiwari in BigQuery, Data Warehousing

Today, companies generate, store and manage huge volumes of data. Storing and querying such volumes of data can be costly and time-consuming, especially for an organization that doesn’t have the…

DATE_ADD function in BigQuery – Syntax and Queries Explained

September 9th, 2021 By Pratik Dwivedi in BigQuery, Data Warehousing

BigQuery offers a wide range of functionality to help you get the most out of date and time data. But sometimes, it can be tiring to understand some of its…

Google’s Bigtable vs BigQuery: Key Differences Simplified 101

September 9th, 2021 By Muhammad Faraz in BigQuery, Data Warehousing, Versus

BigQuery and Bigtable are the two most powerful tools in Google Cloud for handling large datasets with ease. While both handle large volumes of data, They serve different purposes. Bigtable…

Google BigQuery CONCAT: 4 Critical Aspects

September 9th, 2021 By Isola Saheed Ganiyu in BigQuery, Data Warehousing

Today, there are a lot of Database software tools on the internet. Unfortunately, most of them are designed to process small-size data.  If you try to analyze complex data on…

Specifying BigQuery Schema Simplified: 3 Simple Ways

September 8th, 2021 By Hitesh Jethva in BigQuery, Data Warehousing

Business organizations receive data from various resources, they generate petabytes of data on a regular basis. With traditional databases, it is difficult to keep track of this data and even…

Google BigQuery Temporary Tables: 3 Comprehensive Aspects

September 8th, 2021 By Syeda Famita Amber in BigQuery, Data Warehousing

More and more organizations are looking to unlock business insights from the data. However, it can be difficult to ingest, store, and analyze that data as it rapidly grows in…

Amazon Redshift Parquet: 2 Easy Methods

September 3rd, 2021 By Karan Singh Pokhariya in Data Warehousing, Redshift

Scanning a lot of data is easy but not necessarily quick. In this dynamic and ever-growing world, it is a necessity for every business to scan and analyze their data…

Understanding Amazon Redshift Timestamps: 5 Comprehensive Types

September 2nd, 2021 By Aditya Jadon in Data Warehousing, Redshift

Enterprises need to analyze their data to make data-driven decisions. A huge volume of data flowing in real-time needs to be handled and Data Analysts need to perform queries as…

Redshift Concat Functions 101: Syntax and Usage Simplified

September 2nd, 2021 By Rakesh Tiwari in Data Warehousing, Redshift

Amazon Redshift is one of the prominent names in the field of Cloud Storage Services. It offers fully managed systems that can service the data warehousing and database needs of…

Firebolt Data Warehouse Simplified 101

July 20th, 2021 By Nicholas Samuel in Data Warehousing

Today, organizations generate huge volumes of data, across verticals, every day. This has led to an increased demand for Data Storage options. Cloud Storage was invented to meet this demand.…

Snowflake vs Redshift vs BigQuery: 16 Critical Differences

May 31st, 2021 By Ofem Eteng in BigQuery, Data Warehousing, Redshift, Snowflake

Venturing into Data Science and deciding on a tool to use to solve a given problem can be challenging at times especially when you have a wide array of choices.…

Snowflake vs Postgres: 5 Critical Differences

May 21st, 2021 By Amit Phaujdar in Data Warehousing, Snowflake, Versus

PostgreSQL is a reliable database management system with a keen focus on SQL compliance and extensibility. PostgreSQL is well suited for various industries and use cases such as web apps,…

Snowflake vs Oracle: Key Differences 2025

May 12th, 2021 By Pratik Dwivedi in Data Warehousing, Snowflake, Versus

With data requirements growing at the speed of light, the ability to not only manipulate data in real-time but also scale along with it is a must-have for most organizations…