Data Warehouse Modeling White Paper 
DataKitchen
DECEMBER 7, 2021
In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations. A distributed data mesh is a better choice. The book will be available from O’Reilly Media here.
CIO Business Intelligence
MARCH 22, 2022
One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Consider deploying analytics-as-a-service .
CIO Business Intelligence
NOVEMBER 4, 2022
MetaBio, which received a 2022 CIO 100 Award , provides a single source for datasets in a unified format, enabling researchers to quickly extract information about various therapeutic functions without having to worry about how to prepare or find the data. At the data pipeline level, scientists use Apigee, Airflow, NiFi, and Kafka.
Octopai
DECEMBER 12, 2021
Metadata management tools help you understand a data asset’s current status, history, and context, and discover how best to use it for the benefit of your organization. Metadata Management is a Strategic Data Imperative Learn why in our white paper which dives deep into the topic Download the White Paper.
Jet Global
APRIL 2, 2019
Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Which problems do disparate data points speak to? Enter data warehousing. Get Insight Now.
Octopai
NOVEMBER 28, 2019
Once upon a time, almost all data had one shape, and it was a rectangle. For data structures that followed the relational database model, which relate to each other by “primary keys” and “foreign keys,” this approach worked well, as long as different databases didn’t have to “talk” to each other, at least not directly.
Alation
MARCH 29, 2022
This led to the birth of separate systems for reporting: the enterprise data warehouse. For the first time, the focus of a system became business questions, where data was denormalized. The request model started to fray. To learn more about self-service, we recommend: White Paper: Self-Service Data Intelligence.
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