Data Engineering Podcast

JUNE 5, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking all of that information into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Go to dataengineeringpodcast.com/atlan today to learn more about how you can take advantage of active metadata and escape the chaos.

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

JULY 10, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Christophe Blefari

JUNE 16, 2023

Why data consumers do not trust your reporting — It is a good illustration of the data journey manifesto. Stakeholders often notice data issues before the data team does. Data warehouses are mutable, this is one of the many root causes proposed by Lucas. Data Documentation 101: Why?

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Data Engineering Podcast

SEPTEMBER 23, 2018

This includes modeling the lifecycle of your information as a pipeline from the raw, messy, loosely structured records in your data lake, through a series of transformations and ultimately to your data warehouse. What is your opinion on the relative merits of a data warehouse vs a data lake and are they mutually exclusive?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Ascend.io

APRIL 7, 2023

Data fabric is a centralized platform architecture originating from a curated metadata layer that sits on top of an organization’s data infrastructure. Every time a new data source is added, the metadata layer is updated to define how and when that data should be used. Increasing speed.

Metadata 52

Metadata Datasets Data Governance Government 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. See our post: Data Lakes vs. Data Warehouses.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. And over time, we’ve invested effort into cleaning up our lineages, simplifying our logic,” said SeatGeek Director of Data Engineering, Brian London. Data lineage can help!

Data Warehouse 52

Data Warehouse BI Data Government 52