DataKitchen

JANUARY 25, 2022

DataOps improves the robustness, transparency and efficiency of data workflows through automation. For example, DataOps can be used to automate data integration. Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake.

Consulting 97

Consulting Recruitment Data Lake Data Engineering 97

Data Engineering Podcast

JANUARY 7, 2024

Summary Data processing technologies have dramatically improved in their sophistication and raw throughput. Unfortunately, the volumes of data that are being generated continue to double, requiring further advancements in the platform capabilities to keep up.

Data Process 147

Data Process Process Data Lake High Quality Data 147

Workfall

JUNE 12, 2023

CDC also plays a crucial role in data integration and ETL processes. It captures incremental changes from transactional databases or other sources, efficiently loading them into data warehouses or data lakes. and we have now migrated the data from our transactional database to the Snowflake data warehouse.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

MAY 14, 2024

Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Ascend.io

DECEMBER 11, 2023

Here’s the deal: for data to truly drive your business forward, you need a reliable and scalable system to keep it moving without hiccups. In other words, you need data orchestration. In this article, we’ll break down what data orchestration is, its significance, and how it differs from data pipeline orchestration.

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

AltexSoft

NOVEMBER 7, 2022

The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. It still remains a leading workflow management tool adopted by thousands of companies, from tech giants to startups. How data engineering works. What is Apache Airflow?

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

phData: Data Engineering

JANUARY 3, 2022

How do I know where this data came from or how it’s being used? How do I maintain all my data pipelines? How do I recreate the environment and data sets from scratch? How do I build confidence and trust in the data products I create? How do I ensure customers aren’t impacted by changes or new functionality?

IT 52

IT AWS Software Engineer Software Engineering 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59