François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? Data As Code is a very strong choice : we do not want any UI because it is an heritage of the ETL period.

Architecture 130

Architecture Technology Google Cloud Metadata 130

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

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. Technical Challenges Choosing appropriate tools and technologies is critical for streamlining data workflows across the organization.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Cloudera

AUGUST 21, 2020

Security needs to be treated at a mission-critical level and data security also needs to be a core part of a business’s strategic approach. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.

Banking 61

Banking Kafka Cloud Storage Government 61