Remove Apache Kafka Remove Big Data Remove ETL
article thumbnail

Big Data – Lambda or Kappa Architecture?

Data Science Blog

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.

Big Data 130
article thumbnail

Navigating the Big Data Frontier: A Guide to Efficient Handling

Women in Big Data

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How data engineers tame Big Data?

Dataconomy

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. They must also ensure that data privacy regulations, such as GDPR and CCPA , are followed.

article thumbnail

Big Data Syllabus: A Comprehensive Overview

Pickl AI

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

article thumbnail

Introduction to Apache NiFi and Its Architecture

Pickl AI

Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration. Its visual interface allows users to design complex ETL workflows with ease.

ETL 52
article thumbnail

The Backbone of Data Engineering: 5 Key Architectural Patterns Explained

Mlearning.ai

There are various architectural design patterns in data engineering that are used to solve different data-related problems. This article discusses five commonly used architectural design patterns in data engineering and their use cases. Finally, the transformed data is loaded into the target system.

article thumbnail

Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. ETL is vital for ensuring data quality and integrity.