Remove Data Lake Remove Data Management Remove Data Warehouse
article thumbnail

Data Integrity for AI: What’s Old is New Again

Precisely

The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning. In the beginning, there was a data warehouse The data warehouse (DW) was an approach to data architecture and structured data management that really hit its stride in the early 1990s.

article thumbnail

Data Warehouses Vs Operational Data Stores Vs Data Lakes – How To Store Your Data For Analytics

Seattle Data Guy

A few months ago, I uploaded a video where I discussed data warehouses, data lakes, and transactional databases. However, the world of data management is evolving rapidly, especially with the resurgence of AI and machine learning.

Data Lake 130
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Customers that require a hybrid of these to support many different tools and languages have built a data lakehouse.

Data Lake 114
article thumbnail

Keep Your Data Lake Fresh With Real Time Streams Using Estuary

Data Engineering Podcast

In this episode David Yaffe and Johnny Graettinger share the story behind the business and technology and how you can start using it today to build a real-time data lake without all of the headache. What is the impact of continuous data flows on dags/orchestration of transforms? Closing Announcements Thank you for listening!

Data Lake 162
article thumbnail

Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. To start, can you share your definition of what constitutes a "Data Lakehouse"?

Data Lake 262
article thumbnail

Realtime Data Applications Made Easier With Meroxa

Data Engineering Podcast

In this episode DeVaris Brown discusses the types of applications that are possible when teams don't have to manage the complex infrastructure necessary to support continuous data flows. You can collect, transform, and route data across your entire stack with its event streaming, ETL, and reverse ETL pipelines.

Data Lake 277
article thumbnail

Charting A Path For Streaming Data To Fill Your Data Lake With Hudi

Data Engineering Podcast

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

Data Lake 130