Striim

AUGUST 31, 2023

Kappa Architectures are becoming a popular way of unifying real-time (streaming) and historical (batch) analytics giving you a faster path to realizing business value with your pipelines. Kappa Architecture combines streaming and batch while simultaneously turning data warehouses and data lakes into near real-time sources of truth.

Data Integration 69

Data Integration Architecture Amazon Web Services Machine Learning 69

Data Engineering Podcast

JANUARY 7, 2022

StreamSets DataOps Platform is the world’s first single platform for building smart data pipelines across hybrid and multi-cloud architectures. Build, run, monitor and manage data pipelines confidently with an end-to-end data integration platform that’s built for constant change.

ETL System 100

ETL System Data Pipeline Data Warehouse Architecture 100

Ascend.io

DECEMBER 21, 2022

The last three years have seen a remarkable change in data infrastructure. ETL changed towards ELT. Now, data teams are embracing a new approach: reverse ETL. Cloud data warehouses, such as Snowflake and BigQuery, have made it simpler than ever to combine all of your data into one location.

ETL Tools 52

ETL Tools ETL System Data Warehouse Data Consolidation 52

ProjectPro

SEPTEMBER 30, 2014

"Hadoop is a key ingredient in allowing LinkedIn to build many of our most computationally difficult features, allowing us to harness our incredible data about the professional world for our users," said Jay Kreps, Principal Engineer, LinkedIn.

Hadoop 52

Hadoop ETL Tools Unstructured Data ETL System 52

Precisely

APRIL 3, 2023

How can an organization enable flexible digital modernization that brings together information from multiple data sources, while still maintaining trust in the integrity of that data? To speed analytics, data scientists implemented pre-processing functions to aggregate, sort, and manage the most important elements of the data.

ETL System 52

ETL System Transportation Architecture Manufacturing 52

Knowledge Hut

NOVEMBER 28, 2023

As a data engineer description, you must be ready to explore large-scale data processing and use your expertise and soft skills to ensure a scalable and reliable working environment. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Monte Carlo

MAY 17, 2023

Stop Revenue Bleeding System Modernization and Optimization 33. Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. “We Data observability can help ensure your experimentation program gets off the ground.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52