Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Edureka

AUGUST 19, 2024

One of the key elements of Azure Data Factory that permits data integration between various network environments is Integration Runtime. It offers the infrastructure needed to transfer data safely between cloud and on-site data storage.

Transportation 40

Transportation Data Integration Data Storage Utilities 40

Ascend.io

DECEMBER 11, 2023

Data orchestration is the process of efficiently coordinating the movement and processing of data across multiple, disparate systems and services within a company. So, why is data orchestration a big deal? It automates and optimizes data processes, reducing manual effort and the likelihood of errors.

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Data Engineering Weekly

MARCH 11, 2023

[link] Data Engineering Weekly Data Catalog - A Broken Promise Data catalogs are the most expensive data integration systems you never intended to build.

Data Engineer 52

Data Engineer Data Engineering Engineering High Quality Data 52

Databand.ai

AUGUST 30, 2023

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. This demands the implementation of advanced data integration techniques, such as real-time streaming ingestion, batch processing, and API-based access.

Data Governance 40

Data Governance Data Cleanse Government Data Science 40

Cloudera

FEBRUARY 11, 2019

Cloudera provides a unified platform with multiple data apps and tools, big data management, hybrid cloud deployment flexibility, admin tools for platform provisioning and control, and a shared data experience for centralized security, governance, and metadata management. 3. Expansion beyond core data management.

Data Management 43

Data Management Management Metadata Government 43

AltexSoft

NOVEMBER 7, 2022

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. There are typically hundreds of workflows in the Airflow production environment. Metadata database. The most common applications of the platform are.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

Netflix Tech

OCTOBER 27, 2020

Netflix Scheduler is built on top of Meson which is a general purpose workflow orchestration and scheduling framework to execute and manage the lifecycle of the data workflow. Bulldozer makes data warehouse tables more accessible to different microservices and reduces each individual team’s burden to build their own solutions.

Data Warehouse 99

Data Warehouse Datasets Data Big Data 99

Ascend.io

MARCH 17, 2023

For data pipeline automation, these previous approaches have foundered on one important barrier: the need to scale. This can be done with unique digital fingerprints that map not just every snippet of data, but the data engineers’ code as well. Let’s outline what these capabilities should look like.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineering 52

Ascend.io

MARCH 17, 2023

For data pipeline automation, these previous approaches have foundered on one important barrier: the need to scale. This can be done with unique digital fingerprints that map not just every snippet of data, but the data engineers’ code as well. Let’s outline what these capabilities should look like.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineering 52

Edureka

JULY 3, 2024

As data volumes explode across enterprises, the struggle to manage, integrate, and analyze it is getting real. Thankfully, with serverless data integration solutions like Azure Data Factory (ADF), data engineers can easily orchestrate, integrate, transform, and deliver data at scale.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

AltexSoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. Okay, data lives everywhere, and that’s the problem the second component solves.

IT 59

IT Data Warehouse Data Governance Data Lake 59