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

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. By using DataOps tools, organizations can break down silos, reduce time-to-insight, and improve the overall quality of their data analytics processes.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 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 Engineer 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 Engineer 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