Data Engineering

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…

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…

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…

Iceberg Architecture Examples: How Iceberg powers data and ML applications

July 25th, 2024 By Radhika Gholap in Data Engineering

In recent years, Apache Iceberg has seen considerable advancements that highlights its growing importance. Major tech companies like Google, Snowflake, and Databricks have increasingly embraced this table format. Google integrated…

How are Apache Iceberg Tables Optimizing Data Lake Management?

July 25th, 2024 By Rahul Thakor in Data Engineering

A data lake is a central storage place for an organization's data in its original format. Unlike data warehouses, data lakes can handle all kinds of data, including unstructured and…

Avro vs Parquet: Which File Format is Right for You?

July 24th, 2024 By Dipal Prajapati in Data Engineering

While working with huge amounts of data, Data serialization plays an important role in the performance of the system. Data Serialization converts complex data structures, such as graphs, trees, etc.,…

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…

Apache Iceberg vs Delta Lake – Key Differences

July 23rd, 2024 By Parvathy Ramakrishnan in Data Engineering

Businesses are increasingly investing in data lakehouses due to their reduced costs, streamlined workloads, support for real-time data processing, and better decision-making. The global data lakehouse market is estimated to…