2020 Data Lake Data Warehouse Modeling 
O'Reilly on Data
FEBRUARY 19, 2021
The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. A Wave of Cloud-Native, Distributed Data Frameworks.
Jet Global
SEPTEMBER 4, 2020
Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.
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KDnuggets
JANUARY 16, 2020
Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility.
Sisense
DECEMBER 23, 2019
AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. There just aren’t enough AI and data science practitioners to go around to tackle this lofty goal. Get money out of your data.
CIO Business Intelligence
NOVEMBER 4, 2022
By 2020, IT had moved roughly 60% of all company data to the cloud — no minor task for an international firm that generated $16 billion in revenue in 2021, employs more than 10,000 people, and holds nine FDA- and EMA-approved drugs with an additional 30 in clinical trials. Much of Regeneron’s data, of course, is confidential.
Sisense
JULY 8, 2020
Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.
CIO Business Intelligence
SEPTEMBER 12, 2022
Data engine on wheels’. To mine more data out of a dated infrastructure, Fazal first had to modernize NJ Transit’s stack from the ground up to be geared for business benefit. Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases.
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