Data Engineering

Top 10 Data Modeling Best Practices You Simply Can’t Ignore

February 23rd, 2025 By Srishti in Data Engineering

You often find yourself caught in data complexity issues like data complexity, communication breakdowns, and data quality issues, making it tough for your teams to handle data modeling. Data modeling…

What is Data Orchestration?[+Steps, Components, Tools]

February 21st, 2025 By Asimiyu Musa in Data Engineering

This guide dives into data orchestration, its components, tools, importance, and best practices in data. It can be defined as the process or a tool that manages data-related activities. It…

Iceberg Catalogs: Key Features, Benefits, and Insights You Should Know!

February 21st, 2025 By Srishti in Data Engineering

Imagine you're managing a massive lake of data, but without a solid catalog, you find yourself: Facing difficulty in data discovery as data is scattered makes it hard to find…

How to Build a Modern Data Team Structure?

February 16th, 2025 By Khawaja Abdul Ahad in Data Engineering

It is the 21st century and you are leading a fast-growing fintech startup that is about to hit a breaking point. The data team has doubled in size over six…

What is Google Dataflow?

February 7th, 2025 By Raju Mandal in Data Engineering

Have you heard of the Google Cloud Platform, offering a completely managed stream and batch data processing service? Well, this modern data engineering technology plays an essential part in dealing…

What Is ETL Data Mapping And Why Should You Know About It?

February 7th, 2025 By Vishal Agrawal in Data Engineering

In today’s data-driven world, businesses rely solely on data to make informed decisions. For this, they need to efficiently extract, transform, and load (ETL) vast amounts of data. While ETL…

What is ETL Data Modeling? The Why’s and How’s

January 31st, 2025 By Muhammad Usman Ghani Khan in Data Engineering

Businesses rely on data to drive decisions, uncover trends, and stay ahead of the competition. But raw data is often messy, scattered across multiple sources, and difficult to analyze effectively.…

What Are ETL Pipelines? Steps, Benefits, and Use Cases

January 27th, 2025 By Radhika Gholap in Data Engineering, Data Pipeline

In today’s fast-paced digital landscape, businesses face the daunting challenge of extracting valuable insights from large amounts of data. The ETL (Extract, Transform, Load) pipeline is the backbone of data…

Streamlining Success: The Complete Guide to Data Pipeline Optimization

January 27th, 2025 By Muhammad Usman Ghani Khan in Data Engineering, Data Pipeline

Is your business incapacitated due to slow and unreliable data pipelines in today's hyper-competitive environment? Data pipelines are the backbone that guarantees real-time access to critical information for informed and…

What Is the Role of LLM in Data Engineering Evolution?

January 10th, 2025 By Gagandeep Kaur in Data Engineering

Let’s face it: Data engineering is like playing Tetris, always moving objects around to fit them into the right places. The data is never static; pipelines, schemas, transformations, workflows, and…

The Future of Data Engineering Is Here—5 Trends You Can’t Ignore in 2025!

January 9th, 2025 By Sid Lasley in Data Engineering

Have you ever felt like data engineering is evolving at the speed of light? With new tech emerging almost daily, it's no surprise that staying ahead of the curve is…

Mastering Data Migration: Risks, Challenges, and Proven Strategies for Success

December 30th, 2024 By Muhammad Usman Ghani Khan in Data Engineering

Businesses that want to become efficient, effective in their decision process and relevant in the current market must necessarily consider data migration as a top priority. It allows them to…

What Is a Streaming Data Pipeline: Key Features & Use Cases

December 20th, 2024 By Vishal Agrawal in Data Engineering, Data Pipeline

In this fast-paced digital era, multiple sources like IoT devices, social media platforms, and financial systems generate the data continuously and in real-time.  Every business wants to analyze these data…

Mastering Data Consolidation: Benefits, Techniques, and Challenges

December 20th, 2024 By Hafiz Umer Draz in Data Engineering

Introduction Floundering with data fragmentations across various systems? For businesses trying to thrive in a competitive world, seamless access to unified and real data is no longer optional but inevitable.…

The Data Engineering Wrap-Up: 2024’s Biggest Trends

December 19th, 2024 By Sid Lasley in Data Engineering

With the year 2024 nearing its end, it is time to examine the significant trends and advancements that have impacted the field of data engineering. If you’re like me, you’ve…

Simplifying Business Data: The Power of Data Centralization 

December 15th, 2024 By Sarang Ravate in Data Engineering, Data Strategy

There is no denying the fact that in the modern business world, information reigns supreme because that is what is crucial in making decisions. The problem comes when this information…

Databricks Overwrite: Are You Leveraging Its Full Potential?

December 15th, 2024 By Srishti in Data Engineering

Your organization's data requirements are quite special in nature. As the volume and complexity of the data rises, your organization persistently seeks ways to obtain insightful information from everyday updates…

What are Databricks Materialized Views and How to Boost Query Performance Using Them?

November 15th, 2024 By Christina Rini in Data Engineering

Accessing and performing large volumes of data is crucial in data analytics and engineering. As datasets grow larger and more complex, executing queries repeatedly can become a bottleneck, slowing down…

How to Use MySQL ALTER TABLE command?

November 11th, 2024 By Christina Rini in Data Engineering

MySQL is the most popular open-source relational database management system (RDBMS) developed by Oracle Corporation, and it has become a staple for developers and data professionals.  It is very important…

Understanding Conceptual vs Logical vs Physical Data Models for Effective Databases

November 11th, 2024 By Khawaja Abdul Ahad in Data Engineering

Consider designing a skyscraper. You would first need to create a high-level design. Next, you would create detailed plans for each floor. Lastly, you would choose the building materials and…