Implementing Star Schema for Data Modelling in Warehouses January 27th, 2022 By Harsh Varshney in Data Strategy This blog will show you everything about Star Schema Data Modelling and its comparison with different types of Schemas including Star Schema. Below are the three primary types of Multidimensional…
What Is Data Automation: Key Concepts, Examples & Steps Explained June 11th, 2023 By Abhishek Duggal in Data Automation, Data Engineering Businesses typically generate and store colossal amounts of data from which they derive meaningful insights for faster and better decision-making using business intelligence (BI). Because of the variety and complexity…
Google BigQuery Vs SQL Server: 8 Critical Differences January 27th, 2022 By Vishal Agrawal in BigQuery, Data Warehousing, Versus Do you want to find the best database software? Are you unsure whether Google BigQuery or Microsoft SQL Server is best for you? It is impossible to determine whether Google…
Amazon Redshift vs Redshift Spectrum: 6 Comprehensive Differences January 20th, 2022 By Arsalan Mohammed in Data Warehousing, Redshift, Versus Amazon Redshift is one of the most popular Data Warehouse solutions that provide a wide range of functionality along with efficiency and ease of use. Amazon Redshift Spectrum is an…
Snowflake Data Types: A Deep Dive into 6 Essential Varieties July 10th, 2020 By Shruti Garg in Data Warehousing, Snowflake Snowflake provides support for the standard SQL data types (with a few restrictions) for use in columns, local variables, expressions, and parameters. Every column in a table will have a name…
Working with MongoDB Oplog: 3 Comprehensive Aspects March 12th, 2021 By Amit Phaujdar in Database Management System, MongoDB MongoDB Oplog happens to be a special collection that keeps a record of all the operations that modify the data stored in the database. The Oplog in MongoDB can be…
Building a Data Science Tech Stack: A Comprehensive Guide December 12th, 2020 By Vivek Sinha in Data Strategy The field of data science has evolved to a stage where no organization can ignore it while setting up their data science tech stack. Organizations use machine learning not only…
Kafka Event Driven Architecture for Seamless Streaming January 19th, 2022 By Shubhnoor Gill in Data Warehousing, Kafka An Event Driven Architecture (EDA) is a microservices-based architectural paradigm that is becoming more prominent with rising in Big Data and Cloud environments. This isn't just a coincidence. From the standpoint…
Google Cloud SQL vs BigQuery: Key Differences Simplified January 31st, 2022 By Nicholas Samuel in BigQuery, Data Warehousing, Versus In the ever-evolving landscape of cloud computing, businesses are inundated with choices when it comes to managing their data. Among the most prominent options are Google Cloud SQL and BigQuery—two…
Everything You Need to Know About Elasticsearch Ingest Pipeline April 19th, 2022 By Sanchit Agarwal in Data Engineering, Data Pipeline Extracting data from data sources has always been a challenge for organizations worldwide. One of the popular free and open-source tools for creating Ingestion pipelines is ElasticSearch. It acts as…
Easy Elasticsearch and Oracle Data Connection (3 Steps Explained) February 21st, 2023 By Muhammad Faraz in Data Integration Are you tired of sifting through mountains of tables in your Oracle database, struggling to find the information you need? If so, you're not alone. Many businesses today are grappling…
Understanding Data Modelling in Python: 4 Critical Aspects April 27th, 2022 By Nidhi Bansal in Data Strategy In the Python programming language, each entity is treated as an object. Moreover, unlike other programming languages like C or Java, Python does not work with primitive data or non-primitive…
How to Stop or Kill Airflow Tasks: 2 Easy Methods July 29th, 2022 By Vidhi Shah in Data Strategy In today’s data-driven world, enterprises extensively use data pipelines to enable quick data exploration for essential business insights. Pipelines created around extract, transform, and load (ELT) processes pose a challenge…
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,…
Understanding Big Data Processing: 2025’s Ultimate Guide May 31st, 2022 By Pranay Kumar in Data Strategy In real-word, most of the data is unstructured, making it difficult to streamline the data processing tasks. And since there is no end to the data generation process, collecting and…
How Kafka ETL Simplifies Data Processing from Extraction to Loading October 12th, 2020 By Divij Chawla in Data Integration, ETL, Kafka With Traditional ETL no longer being able to meet the demands of the future, businesses across the world have moved on to the paradigm of real-time streaming ETL, which works…
A Complete Guide to Airflow S3 Connection Simplified February 18th, 2022 By Syeda Famita Amber in AWS, Data Integration Airflow is a Task Automation tool. It helps organizations to schedule their tasks so that they are executed when the right time comes. This relieves the employees from doing tasks…
Simplifying Kafka Event Streaming: Easy Steps Explained (with code) March 23rd, 2022 By Shubhnoor Gill in Data Warehousing, Kafka Kafka Event Streaming is becoming essential as data grows across industries. But what exactly is Event Streaming? It enables businesses to: Track events like customer orders or bank deposits in…
Oracle Database Replication: Types, Methods & Top Tools December 23rd, 2021 By Sarad Mohanan in Data Replication, Tutorials Oracle database replication is vital for businesses looking to ensure data consistency, availability, and disaster recovery across multiple locations. With Oracle's robust set of replication tools, companies can efficiently synchronize…
Critical Kafka Producer Config Parameters Simplified March 3rd, 2022 By Raj Verma in Data Warehousing, Kafka Organizations today have access to a wide stream of data. Apache Kafka, a popular Data Processing Service is used by over 30% of Fortune 500 companies to develop real-time data…