The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 8 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Stanek: Hadoop and data warehouses are where data goes to die
“With all the investment in Hadoop and this and Hadoop that, you know, most companies are still data bankrupt. You know, Hadoop or Data Warehouse or whatever is a place where data goes to die”
Naous: Legacy BI and Hadoop are only practical for executive decisions
“Well, you can say maybe we should use Hadoop or BI. Unfortunately, these are kind of older generation tools. They require specialized skills and abilities to be able to use them. And so they need armies of analysts to use. These are really only affordable for …”
Stanek: Business users prefer spreadsheet interfaces over Spark and Hadoop
“Some of the most frequently used kind of data analytics tools extremely basic, because they actually look and feel like sheet of paper, like two-dimensional sheet of paper, and you know, so that's the problem with analytics, that on one hand, we have, you know…”
Moghe: Spark and Hadoop do not replace existing data warehouses
“Spark doesn't subsume data warehousing. Hadoop doesn't subsume, you know, streaming. So they're just like different technologies for different jobs.”
Nguyen: Big Data Progress Is Driven by Cheaper Tech, Not Smarter People
“We don't necessarily get smarter over time. It's just that certain technologies get cheaper. They get, they become more available. So machine learning algorithms have always been around. The data that exists that you could collect has always been around. But i…”
Legacy Hadoop tools like Hive, Pig, and Mahout now run on Spark
“So in particular you know, one of the things we saw is many of the projects that were built on top of Hadoop, such as Hive, which is a SQL processing at scale and Pig and Mahout for machine learning are starting to run on top of Spark as well, so that users of…”
Matei Zaharia interned at Facebook in 2007 when it had 300 employees
“I was a PhD student at UC Berkeley, and we actually started working with Hadoop users back in 2007. And I did, for example, an internship at Facebook when Facebook was only about 300 people and they were just starting to set up Hadoop.”