Data Ingestion Architecture

Data ingestion architecture refers to the framework and processes involved in collecting, importing, and processing data from various sources into a data storage system, such as a data warehouse or data lake. This architecture is crucial for organizations aiming to leverage data for analysis and decision-making. It encompasses various methods, including batch processing and real-time streaming, to ensure data is efficiently and accurately ingested. Effective data ingestion architecture not only simplifies the integration of diverse data sources but also enhances data quality and accessibility, ultimately supporting data-driven initiatives across the organization.

Big Data Architecture Concepts

Analytics Vidhya

With the advancement of technology, the volumes of data organisation’s collect have increased exponentially. A big data architecture is used to ingest, process and analyse data that is too…

Building a Scalable and Open-Source Data Lake End to End Architecture :

Level Up Coding

Data Ingestion : Using Change Data Capture ( CDC ) with Debezium to stream data from MySQL transaction tables into Kafka topics, ensuring real-time data ingestion. Data Storage : Persisting…

Data Engineering: Incremental Data Loading Strategies

Towards Data Science

Years of serving as a data engineer and analyst working on integrating many data sources into enterprise data platforms, I managed to encounter one complexity after another when trying to incrementall...

The Data Mesh architecture

Towards Data Science

The architecture of data is not just a technical architecture but is also an organizational structure, therefore, making it a key factor for building any data empire. Over time there have been…

Data ingestion is (almost) a solved problem

Towards Data Science

Ask anyone who has been involved in a data related job over the past 10–15 years what is the most boring task they would rather avoid, and chances are many would answer ‘data ingestion’. Everyone…

Understanding Data Lineage: From Source to Destination

Towards AI

I went to a restaurant yesterday, “Anthera.” After eating my fourth or fifth piece of pepper chicken, which, by the way, was delicious, I started to be amazed by our capability to digest and savor it....

Real-Time Message Ingestion to Big Data Platform

Better Programming

A practice to ingest the data in real-time from Kafka cluster to the Hadoop/HDFS platform Photo by Joshua Sortino on Unsplash It is quite a common requirement to ingest the data from the microservice ...

Using Databricks Autoloader to support Event-Driven Data Ingestion

Towards Data Science

Simplifying incremental ingestion of data into the Lakehouse with Autoloader Continue reading on Towards Data Science

Building a Confidential Data Mesh

Towards Data Science

The most common data engineering architectures are Data lakes and Data warehouses. Both are centralized systems: data from every data-producing entity is pooled into one location with a single data…

Data Management Architectures — Monolithic Data Architectures and Distributed Data Mesh

Towards Data Science

A data management architecture governs how organizations collect, store, secure, arrange, integrate and use data. A good data management architecture provides clarity about every aspect of data and…

A brief introduction to two data processing architectures — Lambda and Kappa for Big Data

Towards Data Science

Lambda architecture is a data processing technique that is capable of dealing with huge amount of data in an efficient manner. The efficiency of this architecture becomes evident in the form…

Architecting Hadoop Storage Service

Analytics Vidhya

With exponential rise in ingestion and storage of big data, there is a dire need to carefully architect the Storage for faster querying experience and to avoid query costs. And at some point of time…