Recent Articles

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…

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…

Mastering Data Ingestion in Your Apache Iceberg Lakehouse

July 17th, 2024 By Raju Mandal in Data Integration

Every data-centric organization uses a data lake, warehouse, or both data architectures to meet its data needs. Data Lakes bring flexibility and accessibility, whereas warehouses bring structure and performance to…

Apache Iceberg vs Parquet – Comparing Table and File Formats

July 15th, 2024 By Srujana Maddula in Data Strategy

Apache Iceberg and Parquet are popular storage formats in the big data industry. However, they are also often confused terms. So today, we’ll compare these two storage formats, their features,…

What Are Data Lakes? Components, Challenges & Best Practices

July 15th, 2024 By Raju Mandal in Data Strategy

In this information age, there has been explosive growth in the rate and type of data generated daily. From mobile devices and IoT sensors to our online content, unprecedented amounts…

What is Snowflake Horizon? Key Features, Benefits & Use-Cases

July 15th, 2024 By Suraj Poddar in Data Warehousing, Snowflake

Has it ever occurred to you that the volume of data your business processes daily is too overwhelming? You are not alone. So many companies need help in managing and…

Data Analyst Sports: 4 Critical Responsibilities

July 14th, 2024 By Talha in Data Strategy

It is no secret that data is the driving force of most industries today and the field of Sports is not an exception. An enormous amount of data is generated…

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…

Building Data Lake in Apache Iceberg with MySQL CDC

July 12th, 2024 By Dipal Prajapati in Change Data Capture CDC

Building a data lake for reporting, analytics, and machine learning needs has become general practice. Data lakes allow us to ingest data from multiple sources in their raw formats in…

How to Create Streamlit Apps on Snowflake? – A Step by Step Guide

July 10th, 2024 By Srujana Maddula in Data Warehousing, Snowflake

The choice of data management system determines how quickly and in real-time you can store and access information. Some cloud database architectures, like Snowflake, offer a scalable and flexible environment…

Snowpipe Alternatives You Should Consider for Your Data Needs

July 10th, 2024 By Arjun Narayan in Data Integration, Snowflake

While you can use Snowpipe for straightforward and low-complexity data ingestion into Snowflake, Snowpipe alternatives, like Kafka, Spark, and COPY, provide enhanced capabilities for real-time data processing, scalability, flexibility in…

How to Connect Postgres to Google Sheets: 5 Easy Methods

July 9th, 2024 By Skand Agrawal in Data Integration, PostgreSQL

KEY TAKEAWAYS: Method 1: Hevo Data Automated Migration Offers a fully automated, no-code data pipeline solution capable of handling large-scale, continuous, and near real-time syncing of PostgreSQL data to Google…

Snowflake Terraform Integration Made Easy

July 8th, 2024 By Roopa Madhuri G in Data Warehousing, Snowflake

Managing infrastructure manually across multiple cloud providers leads to consistency, deployment delays, and difficulty in scaling. You need a solution that automates infrastructure provisioning, ensures consistency, and supports rapid deployment…

Snowflake Snowpipe Azure Integration: Real-Time Data Ingestion Made Easy

July 5th, 2024 By Arjun Narayan in Data Integration, Snowflake

Managing data ingestion from Azure Blob Storage to Snowflake can be cumbersome. Manual processes lead to inefficiencies and potential errors while also increasing operational overhead.  But what if you could…

Snowflake Arctic: Getting Started with Snowflake’s new LLM

July 5th, 2024 By Rashmi Joshi in Data Warehousing, Snowflake

Snowflake launched its new open-source, “state-of-the-art ” large language model, Snowflake Arctic, in April 2024. The data cloud company announced that the primary idea behind this innovation was to simplify…

Apache Iceberg Table Format: Comprehensive Guide

July 5th, 2024 By Radhika Gholap in Data Strategy

According to the World Economic Forum*, by 2025, the world is expected to generate 463 exabytes of data each day. Here are some key daily statistics: 500 million tweets are…

Snowflake Snowpipe: The Ultimate Tool For Data Loading

July 5th, 2024 By Roopa Madhuri G in Data Integration, Snowflake

Data practitioners often need manual intervention to load large volumes of data into Snowflake in near real-time. Traditional batch loading can be slow and intensive and may lead to latency…

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,…