data warehouse

“The term data warehouse is now an oxymoron. Because data cannot be warehouse.”

“The data warehouse is not capable of doing very large analyses for just, you know, on a whim by anybody who might happen to ask a question”

“If I need to, if I have a new data set, somebody hands me ten billion rows of data, and I want to do an analysis on it, you know, to get a data warehouse up and running, or to add that to an existing data warehouse is a non-trivial thing to do. It takes a long…”

“In practice, the most common use of data warehouses is to support business intelligence dashboards.”

“The additional cost of compute and storage to replicate the extra data, to do those steps, those transformation steps inside the warehouse Are so small now, you know, they're less than what it's going to cost you to pay your data engineer for a week to build y…”

“The tools that you use to manage data and analyze data are actually getting simpler over the last 10 years. You don't need as many different things because a few tools, most importantly the data warehouse, Have gotten so much better over the last 10 years that…”

“We have customers who run billing out of their data warehouse.”

“If we think back to BI tools, say five, certainly 10 years ago, you would sort of beg for a CSV and God help you if the data, if the insight you weren't, the insight you were looking for was not in that CSV, you were sort of screwed. But now thanks to, you kno…”

“Where we are today, the data lake can kind of do anything. But it also probably takes more work to do anything. Whereas the data warehouse is, has a more constrained set of use cases, but it is much easier to get up and running for those constraints set of use…”

“When we talk about the modern data stack, we think about what's really four layers. So there's data ingestion. There's the data warehouse. There's data transformation or like taking all that raw data and like turning it into something valuable. And then there'…”

“There's a class of tools that takes the data that is in your data warehouse and pushes it back to operational systems. And I think that you will, as soon as that starts happening, you can automate the entire process and all of these technologies become, you kn…”

“What's happening now or over the past, you know, five or so years, the, Transformation step now happens inside the data warehouse and it happens in SQL. And because of that, it is now accessible to a dramatically larger number of people.”

“If you land data in your warehouse, it is very hard to ever have it go away completely.”

“So slowly what's happening is that the open source realm An ecosystem is emerging where you can do all of your analytics in this lake house paradigm, and you don't, eventually it will be the case that you will not need all these other, you know, proprietary ol…”

“We've moved away from, okay, I'm going to run a few, set up a warehouse and get a few reports and get an insight into the operation of my organizations to actually I want to run, you know, include ML, a data-driven way of solving problems into every feature of…”

“And I think this kind of funny war between warehouse and lake and web model We should access the data that that seems to me a little bit irrelevant because both of those access models are very acceptable.”

“Reverse ETLs change this paradigm by closing the loop. So these tools enable companies to pipe the transformed unified data from the warehouse back into the upstream business systems from which the data was generated.”

“Data repositories, data warehouses, they all argue that just move all of your data in one place, and it's going to solve all of your problems. We've been hearing that promise for the last 25 years, and it's never solved all of our problems, and it never will.”

“Storage is cheap, but compute is not. And if you are preparing your data in a data warehouse, you're using compute, and your bill is going to get pretty high.”

“Some companies do have maybe the ML engineers access data more directly from maybe the data warehouse, which was things I saw like at Facebook.”