Data Engineering

8 Best Azure ETL Tools for Data Engineers to Consider in 2025

September 27th, 2024 By Kamlesh in Data Engineering

Moving data efficiently in Azure isn’t just about picking any ETL tool—it’s about finding one that fits my workflow without adding complexity. If you’ve ever dealt with slow data pipelines,…

Understanding Modern Data Architecture

September 17th, 2024 By Asimiyu Musa in Data Engineering

Organizations have begun to built data warehouses and lakes to analyze large amounts of data for insights and business reports. Often time they bring data from multiple data silos into…

Top 5 Kafka Tools for Data Engineers in 2025

September 13th, 2024 By Sarad Mohanan in Data Engineering

As the dependency on high-quality, real-time data availability increases, the need for event/data streaming tools becomes increasingly crucial. Apache Kafka has become one of the most trending event streaming platforms,…

Airflow Architecture: 101 on Workflow Orchestration

September 11th, 2024 By Chirag Agarwal in Data Engineering

Data pipelines and workflows have become an inherent part of the advancements in data engineering, machine learning, and DevOps processes. With ever-increasing scales and complexity, the need to orchestrate these…

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…

Building a Successful Data Migration Team

September 6th, 2024 By Khawaja Abdul Ahad in Data Engineering

Did you know that Netflix is one of the biggest clients for AWS? They did not just push a button when they shifted their entire data infrastructure. It took them…

What is a Modern Data Stack? – Everything You Need to Know 

September 6th, 2024 By Srujana Maddula in Data Engineering

Building an efficient data stack that can handle big data is no small feat, whether due to growing data demands or operational costs. A modern data stack solves these problems…

Informatica vs Snowflake: Which Tool to Choose?

September 5th, 2024 By Nitin Birajdar in Data Engineering

Nowadays, businesses heavily rely on data to make informed decisions. Choosing the right tool and data management platform can make or break the business. From small startups to large enterprises,…

Alteryx vs Matillion: A Side-by-Side Detailed Comparison

September 5th, 2024 By Suraj Poddar in Data Integration, Data Pipeline

Data is the new currency in today's world, helping industries make decisions and innovations. To use data to its full potential, organizations require powerful tools to manage, transform, and analyze…

How to Perform Airflow Oracle Connection?

September 1st, 2024 By Khawaja Abdul Ahad in Data Engineering

Imagine putting hours into manually handling data tasks only to discover that one small mistake has caused the entire process to fail. Yes, it is frustrating. This is why automation…

Airflow vs Azure Data Factory: Guide to Choose the Right Tool

September 1st, 2024 By Arjun Narayan in Data Engineering

Managing and orchestrating data workflows efficiently is crucial in today's data-driven world. As the amount of data constantly increases with each passing day, so does the complexity of the pipelines…

Informatica vs MuleSoft: Which Data Integration Tool is Right for You?

August 23rd, 2024 By Roopa Madhuri G in Data Engineering

With growing data and business needs, having an efficient data integration tool to migrate and manage your data has become crucial. Almost every organization keeps its data in different locations,…

Airflow vs NiFi: Choosing the Right Tool

August 23rd, 2024 By Kamlesh in Data Engineering

In the modern, data-driven world, efficient workflow automation and data pipeline orchestration are crucial for any organization connected to complicated data systems. Whether a data engineer, IT professional, or decision-maker…

Building a Data Engineering Team: Strategies and Best Practices

August 22nd, 2024 By Usama Hameed in Data Engineering

Having a robust data engineering team is crucial for organizations to extract maximum value from their data assets. A well-structured data engineering team can streamline data pipelines, ensure data quality,…

Tableau Semantic Layer: A Detailed Guide

August 21st, 2024 By Radhika Gholap in Data Engineering

Today’s data era is all about collecting data from multiple sources and analyzing it to extract valuable business insights. However, with the vast amounts of data generated daily, general SQL…

dbt vs Airflow: A Comprehensive Guide

August 21st, 2024 By Muskan Kesharwani in Data Engineering

Data has become the foundation of any successful business. The ability to efficiently extract, transform, and load data for analysis is crucial for making informed data-driven decisions. Therefore, the tools…

How to Extract Snowflake Data Observability Metrics Using SQL

August 21st, 2024 By Asimiyu Musa in Data Engineering

Ensuring the quality and reliability of data is crucial in today’s data-driven world, as it is essential for making informed decisions and improving operational efficiency. This is where data observability…

AWS DMS CDC Oracle: Configuration, Limitations, and Alternatives

August 5th, 2024 By Chirag Agarwal in Change Data Capture CDC, Data Engineering, Data Streaming

In today’s fast-paced data landscape, real-time data replication and synchronization are critical for maintaining operational efficiency and making timely decisions. AWS Database Migration Service (DMS) offers a comprehensive database migration…

AWS DMS Redshift: Migrate Data to Redshift using AWS DMS

August 2nd, 2024 By Suraj Poddar in AWS, Data Engineering, Redshift

In the modern data-centric world, efficient data transfer and management are essential to staying competitive. AWS offers robust tools to facilitate this, including the AWS Database Migration Service (DMS).Most businesses…

Data Lake vs Delta Lake: Which is Better for Your Data Strategy?

July 31st, 2024 By Martina Šestak in Data Engineering

The fast-growing pace of big data volumes produced by modern data-driven systems often drives the development of big data tools and environments that aim to support data professionals in efficiently…