Data Engineering

Using Emerging Technologies to Address Data Lake Challenges

July 23rd, 2024 By Adedotun Adeboye in Data Engineering

The term “Data Lake” was first introduced by James Dixon in 2010 as a form of storage to cope with evolving data needs due to advancements in IT and IoT.…

A Deep Dive into Data Lakehouses

July 18th, 2024 By Ahmed Shaaban in Data Engineering

The term “Data Lakehouse” is quite common nowadays. The new concept promises to address the failures of data warehouses and data lakes and help support the workloads of both business…

Top 10 Leading Data Lake Tools in 2025: Choose the Right One

July 12th, 2024 By Talha in Data Engineering

Are you looking for a data lake tool that is scalable, cost-efficient, and accessible, can store your business’s historical data, and can help you perform intelligent analytics?  No worries. To…

How to Adapt Apache Iceberg for High-scale Streaming Data

July 4th, 2024 By Srujana Maddula in Data Engineering, Data Streaming

Real-time data requires processing and analytics tasks to be performed within seconds. Organizations often struggle to store and process this data quickly enough. High throughput, large volumes, different data formats,…

How RAG Architecture Can Enhance Your Application’s Data Retrieval

July 4th, 2024 By Raju Mandal in Data Engineering

Retrieval-augmented generation (RAG Architecture) enhances response generation of a Large Language Model (LLM) by incorporating external information retrieval. It searches a database for information beyond the model's pre-trained knowledge base,…

Databricks SQL: Everything to Know

July 3rd, 2024 By Sarthak Bhardwaj in Data Engineering

Databricks SQL is an efficient platform for querying and analyzing large datasets. Its SQL editor, interactive dashboards, and robust BI tool integration features can help you streamline data exploration and…

Oracle Real Time Replication: Simple Steps to Set Up

June 26th, 2024 By Talha in Data Engineering

Are you looking for a simple method to set up real-time replication for data in your Oracle database? If yes, you are in the right place. Real time replication is…

Manage Date/Time Values Using EXTRACT From Oracle Function

June 26th, 2024 By Dimple M K in Data Engineering

Effective data management requires accurate data capture, storage, processing, and analysis. Date and time values are critical in organizing and filtering data, providing a foundation for efficient data processing. Oracle’s…

Understanding Oracle GoldenGate: A Comprehensive 101 Guide

June 26th, 2024 By Skand Agrawal in Data Automation, Data Engineering

As your business grows, so does the complexity of your data ecosystem. In today's data-driven world, managing and integrating this massive volume of data is critical yet challenging. You need…

What is Data Streaming? A Comprehensive Guide 101

June 7th, 2024 By Pratik Dwivedi in Data Engineering, Data Streaming

Real-time data is the need of the hour for businesses to make timely decisions, especially in cases of fraud detection or customer behavior analysis. Relying on traditional batch processing is…

How to Setup Spark Real-time Streaming? 2 Easy Methods

June 7th, 2024 By Ishwarya M in Data Engineering

In today's data-driven world, a colossal amount of data is generated from sensors, IoT devices, social networks, online transactions, and more. In order to harness the power of continuously generated…

6 Must-know Advantages of Data Replication

June 7th, 2024 By Preetipadma Khandavilli in Data Engineering

An automated data replication process is particularly essential for data-driven organizations as they produce a colossal amount of digital information daily. However, the advantages of data replication are not limited…

Data Pipeline Architecture: Diagrams & Best Practices

June 7th, 2024 By Sharon Rithika in Data Engineering, Data Pipeline

Data pipelines play a vital role in modern data management. They connect various data sources within an organization to those who need them. The ability to move data quickly and…

Data Pipeline Lambda: A Comprehensive Guide 101

June 7th, 2024 By Skand Agrawal in Data Engineering, Data Pipeline

Organizations today process and transform a large amount of data with ETL (extract, load, and transform) pipelines. But, loading and transforming this big data is time-consuming. However, sometimes, you do…

Role of Data Analytics in Engineering: 4 Critical Use Cases

May 31st, 2024 By Jayesh Asrani in Data Engineering

Data plays an important role in most of the decision-making processes be it related to business or even Engineering processes. It was difficult in the past to set up and…

What is Data Processing?: A Comprehensive Guide 101

May 17th, 2024 By Dimple M K in Data Engineering

As the world is becoming more data-driven day by day, the need to gain valuable insights from data is also growing. Nowadays, Data Analytics has grown in popular demand in…

ETL vs Data Pipeline : What Are the Key Differences?

April 26th, 2024 By Abhinav Chola in Data Integration, Data Pipeline, ETL

The term "ETL" describes a group of processes used to extract data from one system, transform it, and load it into a target system. A more general phrase is "data…

What Are Observability Pipelines: The Only Guide you Need

April 5th, 2024 By Anmol Baunthiyal in Data Engineering, Data Pipeline

Keeping your data's health up to date is the biggest challenge organizations face today. It's the only way to ensure your information assets are fit for purpose, driving accurate insights.…

Vulnerability Assessment for Data Pipelines: Methods and Tips

February 2nd, 2024 By Jalaj Jain in Data Engineering, Data Pipeline

In data-driven organizations, data is used for strategic decision-making, serving customers, and driving innovation. Therefore, securing it from cyber attacks, malware, and other factors becomes crucial. That is where vulnerability…

Authentication of Data Pipelines: Key Strategies to Secure and Control Your Workflow

February 2nd, 2024 By Suchitra Shenoy in Data Engineering, Data Pipeline

Data pipelines have become an integral part of organizational workflows to keep pace with the rapidly evolving landscape of data management and analytics. By systematically processing and transporting data from…