Data Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse Platform
The lakehouse is a new data platform paradigm that combines the best features of data lakes and data warehouses. It is designed as…
The lakehouse is a new data platform paradigm that combines the best features of data lakes and data warehouses. It is designed as…
There are many different data models that you can use when designing an analytical system, such as industry-specific domain models, Kimball, Inmon, and…
Breaking through the scale barrier (discussing existing challenges) At Databricks, we are hyper-focused on supporting users along their data modernization journeys. A growing…
Data powers scientific discovery and innovation. But data is only as good as its data management strategy, the key factor in ensuring data…
従来のデータウェアハウスにおける増分 ETL(抽出・変換・ロード)は、CDC(変更データキャプチャ)ソースでは一般的になりました。しかし、規模、コスト...
Deep Learning (DL) models are being applied to use cases across all industries — fraud detection in financial services, personalization in media, image…
Behind the growth of every consumer-facing product is the acquisition and retention of an engaged user base. When it comes to customer acquisition,…
One of the questions that we often hear from our customers these days is, “Should I develop my solution in Python or R?”…
The global health crisis accelerated the adoption of omnichannel shopping and fulfillment. Consumers spent $861.12 billion online with US merchants in 2020, up…
This is a co-authored post written in collaboration with Moritz Steller, AI Evangelist, at John Snow Labs. Watch our on-demand workshop, Extract Real-World…