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

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g., Conclusion.

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98

Data Engineering Podcast

AUGUST 21, 2022

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. Can you describe what is driving the adoption of real-time analytics?

Lambda Architecture 100

Lambda Architecture MongoDB MySQL Scala 100

Towards Data Science

JANUARY 16, 2024

Evolution of the data landscape 1980s — Inception Relational databases came into existence. Databases were overwhelmed with transactional and analytical workloads. Result: Data warehouse was born. Image by the author Early 1990s — Scale Analytical workloads started to get complex. Data volumes started to grow.

Data Warehouse 63

Data Warehouse Data Architecture Relational Database NoSQL 63

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

Data Engineering Weekly

NOVEMBER 13, 2022

The author narrates how OS-C adopted Data Contract and federated data governance strategy to help fight against climate change. link] Sponsored: Why You Should Care About Dimensional Data Modeling It's easy to overlook all of the magic that happens inside the data warehouse.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

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