Data Lake Data Workflow Designing Metadata 
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. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. What you have to code is this workflow !
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.
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Hepta Analytics
FEBRUARY 14, 2022
We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design. When the business intelligence needs change, they can go query the raw data again. The purpose of the data is not determined.
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. It is commonly employed for compliance monitoring, data lineage, and maintaining historical records.
Knowledge Hut
SEPTEMBER 29, 2023
Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.
Cloudera
AUGUST 21, 2020
Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.
Monte Carlo
MAY 14, 2024
At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.
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