Data Engineering Podcast

JANUARY 21, 2024

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. How has that changed the architectural approach to CDPs?

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Towards Data Science

JANUARY 16, 2024

Evolution of the data landscape 1980s — Inception Relational databases came into existence. Organizations began to use relational databases for ‘everything’. Databases were overwhelmed with transactional and analytical workloads. Result: Data warehouse was born. Architectures became complex.

Data Warehouse 95

Data Warehouse Data Architecture Relational Database NoSQL 95

Data Engineering Podcast

AUGUST 21, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Lambda Architecture 100

Lambda Architecture MongoDB MySQL Scala 100

Rockset

MARCH 19, 2020

With all of these stream processing and real-time data store options, though, also comes questions for when each should be used and what their pros and cons are. I hope by the end you find yourself better informed and less confused about the real-time analytics landscape and are ready to dive in to it for yourself.

Kafka 40

Kafka Database Process SQL 40

Striim

AUGUST 22, 2024

What’s the difference between real-time analytics and streaming analytics? Streaming analytics focuses on analyzing data in motion, unlike traditional analytics, which deals with data stored in databases or data warehouses.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Knowledge Hut

FEBRUARY 27, 2023

Engineers work with Data Scientists to help make the most of the data they collect and have deep knowledge of distributed systems and computer science. In large organizations, data engineers concentrate on analytical databases, operate data warehouses that span multiple databases, and are responsible for developing table schemas.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Monte Carlo

JULY 25, 2022

There’s a lot of content out there about why a data mesh is (or isn’t) the best thing since sliced bread. But one thing’s for sure: if you can’t trust the data powering your analytics architecture, it’s hard to justify the investment.

Government 52

Government Data Architecture Insurance 52