· Sep 1

Data warehouses and data lakes with data from IRIS

In today's landscape, enterprises have grown substantially in scale, amassing vast amounts of data. This data is collected from a plethora of sources including different applications, databases, and other channels. Given the diversity and volume of this data, it's only logical for these enterprises to seek a deeper understanding of what their data entails. Some of the data can be stored in IRIS, and it can be reasonable to be able to add this data to a data lake too.

The Internet now offers many different tools for such tasks, that do not yet support IRIS, but it's achievable. 

What do you think about it, probably someone already needs something like that, or is still in search.

Discussion (7)6
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Great discussion topic, @Dmitry Maslennikov. Having the IRIS Data Platform play a role in all kinds of data warehouse/lake architectures is certainly important. Especially since these architectures have been evolving recently to take advantage of the convergence of systems of record and systems of reference -- i.e. transactional and analytical databases. In short, one can easily make a strong argument that the IRIS Data Platform can be the foundation for most operations on data -- transactions, analytics and machine learning. On top of that, I see a strong opportunity for our developer community to create tools that offer better DataOps capabilities, like orchestrating data transformations with data pipelines, creating data catalogs, and augmenting all these with machine learning tools to automate much of this data engineering work.