BigDataNYC

not very ;) need different visualizations for time-series analysis to follow patterns of events

Hadoop is limited from folks we talk to but a big part in certain use cases. small improvement in bus operations yields big value in revenue & business outcomes; faster dynamic BI is the answer; what google did for web pages someone need to do

Very thought provoking question. Seems like BI is evolving so the answer to this might evolve too. Do you think?

What google did for web pages someone needs to do for BI and DW enabling non IT people to be "the next Billy Beane" #moneyball for enterprises

interesting BI vs. BA & the evolvement of #Storm I personally think that link analytics becomes increasingly relevant

I'm predicting a big topic at Hadoop World will be the difference between BI and Big Data Analytics. It will be a stark contrast.

in-memory no-sql + analytics is becoming more interesting to BI than Hadoop

I think that we are going to see a ton of link/graph building on hadoop to aid in analytic process... question is one of correlation vs. causality at end of day

Wow more great questions. Very thought provoking. Need more than Twitter to deal with this one...

Data Governance, Data Architecure are extremely important. IT has to provide security and governance for #BigData Analytics to suceed

IT drives this imho bc cloud opens up a can of worms wrt security bc it differs from on-prem vs cloud.. very important that SLAs on the front end meet the cloud security SLA

What if an enterprise user generates conclusion based on new self service BI and mis-uses info? There are endless scenarios where that could happen. And I can't think of an auditing system that would stop that.

why isn't there a whitelist / blacklist registry

and I also believe that tools like #chorus may provide for peer review of analytics through visible analytic process

#SelfServiceAnalytics does not equal chaos. It too, can be governed

it's funny that we talk about governance, and yet don't recognize the importance of peer review in science ... proofs versus theorems

Is a data pool, or data ocean, additive, or subtractive to Big Data Infrastructure as you've defined it here?

no brainer on the rise.. the market for big data apps hasn't come to life yet bc the killer app is visualization which is being paced by analytics which is waiting on infrastructure #DWBI #ConvergedInfrastructure retooling

Big Data is only getting bigger, and more disparate :)

the underlying #BigData infrastructure is the enabler of effective and game-changing #analytics - can't have one without the other IMO

also AWS is showing the model for integrating stacks for rapid developer productivity and their next step will be big data apps to be followed by @rackspace @pivotal @ibm @hp etc

Data science should be everyone in the organization according to Florian Zettelmeyer who spoke at #GE event last week

@kelloggschool posted https://twitter.com/KelloggSchool/status/388364388266037250

IMHO Data scientists combine technical know-how & curiosity to analyze massive amts of data to deliver insights/answers to help solve real business problems.

They’re part technologist, scientist, researcher, business analyst, mathematician, statistician, economist and engineer!

I always loved the @josh_wills data scientist definition: Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.

role should be to identify insights that can be productionized and rolled out to business users

Or should i say the "Promise of BI" and DSS going way back.

companies like Platfora are redefining BI and most CIOs want to throw away the old data warehouses and BI techniques and use more agile ways to get data out in the hands of users

here is an article on SD Times http://www.sdtimes.com/content/article.aspx?ArticleID=64227&page=1

well it won't be the old style of BI apps and platforms - too rigid, slow and not user friendly

@kdnuggets wrote: https://twitter.com/kdnuggets/status/390903174376488961

how often are you calling people for data? and then not knowing how it's been transformed [tampered] and whether it's fit for purpose

I agree that we will see the rise of what I call "graph software" which will create the "next Google" bc search is the big problem..clutter is a discovery and navigation problem to "data"

Are enterprises viewing the challenge this way? Really changing the construct.

And the elevation of the second order info, the meta data. interesting

Wow! There are a number of blog posts in this tweet.

I agree and I would add (bc of CrowdChat) we are also CrowdConsumers - both are new categories of a very important & relevant trend #cc #venturecapital dudes

we all do it with @linkedin but don't realize it when we see that certain people are 3 degrees away and then try and figure what the link is and why!

Are the LOB folks were talking about helping in their day jobs with data, the #DataConsumers you're refering too? And again, are we empowering them more effectively?

interesting seeing HR/Recruiters using big data...http://www.cio.com/article/738356/HR_Departments_Invaded_By_Data_Scientists

Tools that can drop inside of an organization's firewall are useful (flexible hosting)

open source world is actually making good strides here - Apache Accumulo fine-grain security capabilities and more recently Sentry from Cloudera - not as fine-grained but more role-based security

I think the point of OpenSource is to avoid the scrutiny to some degree. IT Governance has to play a part with sensitive data. NSA & WikiLeaks being examples.

I think that communicating with their checkbook bc open source dudes want to make money too.. @cloudera is targeting that with CDH

Security is a if not THE top issue - and the one that companies must address. Still have a long way to go - but I agree strides are being made. I finally got on this CrowdChat today thanks to working through our own IT Security experts!;-)

#BigData represents a wealth of security challenges. HDFS hosts a wide variety of formats that can't be dealt w/ the same way. #BIAnalytics layer should limit access as well

Interactive, seems like a key point, might have a partial hypothesis, but those change as new patterns emerge, check a different path

the crowd call agree that Tableau really shines the light on the value of getting at data fast and in many different ways..kills any argument for old model of BI and DW

good distnction - with traditional BI, you model the underlying data to answer predefined questions - interactive analytics allows for iterative investigation of data