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What's After Big Data?
gthuang88 writes: As the marketing hype around "big data" subsides, a recent wave of startups is solving a new class of data-related problems and showing where the field is headed. Niche analytics companies like RStudio, Vast, and FarmLink are trying to provide insights for specific industries such as finance, real estate, and agriculture. Data-wrangling software from startups like Tamr and Trifacta is targeting enterprises looking to find and prep corporate data. And heavily funded startups such as Actifio and DataGravity are trying to make data-storage systems smarter. Together, these efforts highlight where emerging data technologies might actually be used in the business world.
looking to find and prep corporate data
I read as "looking to find and grep corporate data"...
After big data comes bigger data. Why, did you think otherwise?
Don't waste your vote! Vote for whoever you want, unless you live in a swing state it won't matter anyways
It's a perfectly cromulent buzzword
Literally everyone wants nothing more than a big D.
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After big data they will hire people to think and actually produce useful/actionable insights.
After that they will hire thinking machines.
After that .. with the last vestiges of humanity in zoo's for the amusement of machines .. it's anyone's guess.
Think Minority Report-style marketing.
Big Garbage(can). Most of the data is worthless
More buzzwords conjured up by marketing wannabe's.
I'd love these buzzwords creators to define their buzzwords. Would make our world less clueless and a more informative race.
if(Data >= 1TB)
{
bBigData = true;
}
Was that so hard mr.Marketing?
TFA's question answered is in headline
Thank you Dave Raggett
Cloud Data. Now if you'll excuse me, I'm going to create a phony website to attract suckers investors.
Deep Learning is the next marketing buzzword, perhaps with good reason this time.
"When information is power, privacy is freedom" - Jah-Wren Ryel
How do you want it ? Rare, medium or well done ?
Of course!
Stasis is death. Embrace change.
The problem with 'Big Data' is everyone is trying to use it as a substitute for actual hypothesizing and experimentation.
I am not suggesting it isn't useful, it is, and it can be a huge help in identifying non-intuitive relationships that may exist. Its not being marketed that way though! Everyone is trying to sell it as the solution to all their unresolved problems and knowledge gaps.
At the end of the day all it can ever show is correlation, never causation. All the fancy AIs we add on top are really just correlation engines as well. One day real-soon-now WATSON or something like it will diagnose your cancer. It won't 'discover' the cure though, it will just apply the 'KNOWN' treatment that statistically correlates with the best outcome, hopefully excluding some which correlate with especially un pleasant side effects.
Same is true with the financial markets. Big Data alone will never discover a unified theory that explains market behavior. It will probably make a handful of people stupid amounts of money based again or event correlation and speed. As long as those are the drivers though we will remain forever at risk of sudden meltdowns.
Repeal the 17th Amendment TODAY! Also Please Read http://www.gnu.org/philosophy/right-to-read.html
Judging from all the new aggregated travel sites that say they search "all travel sites to get you the best price", my guess is an aggregated big data warehouse that searches "all big data to get you the best target profile for your advertising. Canoe(tm). Search one and done, the best profile for the right price. Guaranteed."
From the linked piece:
This is true, and it provides the context missing from TFS: "Big Data" is over as a marketing term. But as technological term and as far as actual implementation, it is the status quo and forevermore will be.
From a technological perspective, "Big Data" has a simple definition: more data than can be stored on a single machine. And this need will only grow as hard drives and maybe even SSDs plateau while of course enterprise data only grows.
Indeed, TFA itself states (that TFS omitted):
So, from TFA itself: Hadoop is hot, but the term "Big Data" is not.
Ads on the insides of your eyelids, random "disappearances", a stock market crash or two, a bunch of middle-aged White guys who achieved one thing and are now kicking back and raking it in as pundits, WW3, roving bands of thugs allied with motorcycle gangs terrorizing the nation, or any number of other random things that might be benign or catastrophic.
For all intensive purposes, "whom" is no longer a word. That begs the question, "who cares"?
... distributed across a multiple heterogeneous platforms.
Didn't we solve that problem on Linux already? I've never heard of /dev/null getting full have you?
"File to fit, pound to insert, paint to match" - Aircraft Maintenance 101
If you have windows, that recycle bin is going to be REALLY full and I'm not sure how you are going to empty it with just a mouse.
"File to fit, pound to insert, paint to match" - Aircraft Maintenance 101
It's like trainspotting, but for advertising memes.
Gartner is the king/pusher of course. But I think they were actually insightful about this 5 or so years ago. They predicted about 3 year of all hype, no product "cloud", another 3 years of practical, useful cloud infrastructure with nothing really taking advantage of it, and only after that would we see startups (and VC investment opportunities) making use of the cloud to make actual products. I think we're almost there.
Even for hobby programming, the cloud is becoming quite appealing. For example, take a look at this remarkable Mabdelbrot zoom to 10^275. This required 6 core-years to render (6 months wall clock). If you have the patience, the machines sitting idle (perhaps discarded bitcoin rigs) and no fear of power bills, then sure, turn on 3 old high-CPU towers for 6 months. But if you're good at massively parallel coding (and Mabdelbrot rendering is great to learn that!) you can usually get AWS Spot machines for under a penny per core-hour. That means you can get that 6 core-years of CPU for about the price of a midrange geek PC, and you can get thousands of cores in parallel, and be done rendering in a day.
For a hobby project it might be hard to justify spending $hundreds this way, but for a start-up it makes perfect sense. So there's something to the "cloud" IMO if you're trying to do supercomputer parallelism on a shoestring budget, something that's really only become possible in the past couple of years. I'm not sure how cheap 10000 core-hours for $100 is, really, but 10000 cores in parallel for an hour for $100 is something wonderful.
Socialism: a lie told by totalitarians and believed by fools.
What's After Big Data?
Big Brother, and after he finds out what you are guilty of: the Big House. Then comes Big Love with Big Bubba and his Big Little Bubba. Next is Big Money for Big Medical to fix up your Big Rectum.
Look where all this talking got us, baby.
RStudio is an IDE for the R language. When an author conflates that with whatever those other things are, you can be fairly sure whatever he's saying is likely to be up there on the bullshit scale.
[FUCK BETA]
uhh ... "big data" has been around since the 1940s, and solved. It is surprising how many scamming/snake oil companies are out there
Coming up with my own startup is just too hard to do. Instead, can one of you think of a cool technology I can half-assed write in the hopes of getting a huge payout from some monolithic corp decides that they-too want to jump into the hot market of the moment?
Bye!
Big Spock
Full disclosure/shameless plug: I work internal IT for ExtraHop Networks.
Analytics platforms like ExtraHop do the analysis on streams of data in real-time so that what gets sent to the Big Data store (such as Elasticsearch) is structured or clean data that's more immediately useful.
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