Everything Prat Moghe said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Moghe: Big data projects fail when data collection precedes business goals
“When you looked at many big data projects, the ones that fail, Are ones where people have taken this approach of saying, I want to collect all the data, and then I want to figure out what questions I can ask. I want to look for hidden patterns, as opposed to p…”
Pratt Mogai: Mass direct marketing is over
“The days of, you know, mass direct marketing are over.”
Moghe: Big data is defined by decision speed, not storage volume
“I sort of define big data as it's a mindset. It's about being really fast about using data to make decisions. So it's not just about petabytes of data. It's about, you know, how fast can you leverage data to create business outcomes and so that mindset is what…”
Moghe: Enterprise data is shifting to verticalized full-stack applications
“So there's a whole new breed of, ah, we heard this morning, like the full stack, you know, sort of the full stack app. Like verticalized, experiences, everything that matters. I think that's where it's going. I think where it's going is all that data gets surf…”
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.”
Mogai: NYC reduced gunfire and police deployment using predictive data
“You know, like in New York City, I think this was New Year's Eve, and they collected statistics on random gunfire, and they used that data to predict where they should deploy, ah, police so that they could ensure safety, right? And what they realized is that t…”
Pratt Mogai: Big data is difficult to migrate due to deep enterprise integration
“If you look at big data is not a siloed application. It gets infused through the organization. So it's usually part of some operational business process. And it's really hard to lift and shift it into the cloud.”
Pratt Mogai: Big Data 1.0 is a $10B market dominated by incumbents
“One dot O, which is where most of the world is, it's a ten billion dollar market, largely going to a few incumbents, right?”
Moghe: Democratized cloud big data will flatten corporate organizational structures
“I think that's the Google-like or the Facebook-like culture you want to see permeated across all the top 2000 enterprises, and it's not there today. So I think the long-term implication of big data, cloud making it really democratic is access to everyone, flat…”
Prat Moghe: Many major banks remain in traditional data centers
“Like, if you look at the big banks around you, many of them are still in the data center.”
Cazena CEO: Unmonitored cloud spending can hit $50,000 unexpectedly
“Like I have a CFO watching my cloud costs every day. Because if you don't watch them quickly, you spend 50,000 dollars without even knowing it.”
Prat Moghe: Hiring qualified Hadoop DevOps engineers is exceptionally difficult
“Can you actually hire a good Hadoop DevOps engineer? Is it easy? I mean, you saw somebody stand up here saying they're recruiting. There's a reason, and it's because it's really hard to find these people, right?”
Prat Moghe: Provisioning cloud analytics is a dark art
“So just provisioning, provisioning what you need in analytics from the cloud itself is a dark art.”
Prat Moghe: Cloud is not inherently insecure, but default settings are open
“Security is one of those things where people are either completely afraid of the cloud security and say cloud's not secure, which I say that's just not true. Cloud has a lot of great security controls, but the reality is it's a lot of work to take all of those…”
Prat Moghe: Daily enterprise data increments rarely reach petabytes per day
“The daily increment typically be found is usually in a few terabytes a day. It's rarely petabytes a day.”
Moghe: FINRA, NASDAQ, and Capital One are going all-in on cloud big data
“FINRA, NASDAQ, Capital One. I mean, these are like really cutting edge, large companies that have actually retooled themselves, right? And they've said, they're going all into the cloud. They're going to do big data in the cloud.”
Cazena selected Redshift, Greenplum, Cloudera, and RStudio for its data platform
“We picked Redshift and Greenplum for SQL. We picked Cloudetta for Hadoop and Spark. We've added RStudio for data science.”