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Little Data, Big Data and Very Big Data (VBD) or Big BS?
I routinely hear from different people or groups trying to define what is or is not big data

This is an industry trends and perspective piece about big data and little data, industry adoption and customer deployment.

If you are in any way associated with information technology (IT), business, scientific, media and entertainment computing or related areas, you may have heard big data mentioned. Big data has been a popular buzzword bingo topic and term for a couple of years now. Big data is being used to describe new and emerging along with existing types of applications and information processing tools and techniques.

I routinely hear from different people or groups trying to define what is or is not big data and all too often those are based on a particular product, technology, service or application focus. Thus it should be no surprise that those trying to police what is or is not big data will often do so based on what their interest, sphere of influence, knowledge or experience and jobs depend on.

Traveling and big data images

Not long ago while out traveling I ran into a person who told me that big data is new data that did not exist just a few years ago. Turns out this person was involved in geology so I was surprised that somebody in that field was not aware of or working with geophysical, mapping, seismic and other legacy or traditional big data. Turns out this person was basing his statements on what he knew, heard, was told about or on sphere of influence around a particular technology, tool or approach.

Fwiw, if you have not figured out already, like cloud, virtualization and other technology enabling tools and techniques, I tend to take a pragmatic approach vs. becoming latched on to a particular bandwagon (for or against) per say.

Not surprisingly there is confusion and debate about what is or is not big data including if it only applies to new vs. existing and old data. As with any new technology, technique or buzzword bingo topic theme, various parties will try to place what is or is not under the definition to align with their needs, goals and preferences. This is the case with big data where you can routinely find proponents of Hadoop and Map reduce position big data as aligning with the capabilities and usage scenarios of those related technologies for business and other forms of analytics.

SAS software for big data

Not surprisingly the granddaddy of all business analytics, data science and statistic analysis number crunching is the Statistical Analysis Software (SAS) from the SAS Institute. If these types of technology solutions and their peers define what is big data then SAS (not to be confused with Serial Attached SCSI which can be found on the back-end of big data storage solutions) can be considered first generation big data analytics or Big Data 1.0 (BD1 ;) ). That means Hadoop Map Reduce is Big Data 2.0 (BD2 ;) ;) ) if you like, or dislike for that matter.

Funny thing about some fans and proponents or surrogates of BD2 is that they may have heard of BD1 like SAS with a limited understanding of what it is or how it is or can be used. When I worked in IT as a performance and capacity planning analyst focused on servers, storage, network hardware, software and applications I used SAS to crunch various data streams of event, activity and other data from diverse sources. This involved correlating data, running various analytic algorithms on the data to determine response times, availability, usage and other things in support of modeling, forecasting, tuning and trouble shooting. Hmm, sound like first generation big data analytics or Data Center Infrastructure Management (DCIM) and IT Service Management (ITSM) to anybody?

Now to be fair, comparing SAS, SPSS or any number of other BD1 generation tools to Hadoop and Map Reduce or BD2 second generation tools is like comparing apples to oranges, or apples to pears. Lets move on as there is much more to what is big data than simply focus around SAS or Hadoop.

StorageIO industry trends cloud, virtualization and big data

Another type of big data are the information generated, processed, stored and used by applications that result in large files, data sets or objects. Large file, objects or data sets include low resolution and high-definition photos, videos, audio, security and surveillance, geophysical mapping and seismic exploration among others. Then there are data warehouses where transactional data from databases gets moved to for analysis in systems such as those from Oracle, Teradata, Vertica or FX among others. Some of those other tools even play (or work) in both traditional e.g. BD1 and new or emerging BD2 worlds.

This is where some interesting discussions, debates or disagreements can occur between those who latch onto or want to keep big data associated with being something new and usually focused around their preferred tool or technology. What results from these types of debates or disagreements is a missed opportunity for organizations to realize that they might already be doing or using a form of big data and thus have a familiarity and comfort zone with it.

By having a familiarity or comfort zone vs. seeing big data as something new, different, hype or full of FUD (or BS), an organization can be comfortable with the term big data. Often after taking a step back and looking at big data beyond the hype or fud, the reaction is along the lines of, oh yeah, now we get it, sure, we are already doing something like that so lets take a look at some of the new tools and techniques to see how we can extend what we are doing.

Likewise many organizations are doing big bandwidth already and may not realize it thinking that is only what media and entertainment, government, technical or scientific computing, high performance computing or high productivity computing (HPC) does. I'm assuming that some of the big data and big bandwidth pundits will disagree, however if in your environment you are doing many large backups, archives, content distribution, or copying large amounts of data for different purposes that consume big bandwidth and need big bandwidth solutions.

Yes I know, that's apples to oranges and perhaps stretching the limits of what is or can be called big bandwidth based on somebody's definition, taxonomy or preference. Hopefully you get the point that there is diversity across various environments as well as types of data and applications, technologies, tools and techniques.

StorageIO industry trends cloud, virtualization and big data

What about little data then?

I often say that if big data is getting all the marketing dollars to generate industry adoption, then little data is generating all the revenue (and profit or margin) dollars by customer deployment. While tools and technologies related to Hadoop (or Haydoop if you are from HDS) are getting industry adoption attention (e.g. marketing dollars being spent) revenues from customer deployment are growing.

Where big data revenues are strongest for most vendors today are centered around solutions for hosting, storing, managing and protecting big files, big objects. These include scale out NAS solutions for large unstructured data like those from Amplidata, Cray, Dell, Data Direct Networks (DDN), EMC (e.g. Isilon), HP X9000 (IBRIX), IBM SONAS, NetApp, Oracle and Xyratex among others. Then there flexible converged compute storage platforms optimized for analytics and running different software tools such as those from EMC (Greenplum), IBM (Netezza), NetApp (via partnerships) or Oracle among others that can be used for different purposes in addition to supporting Hadoop and Map reduce.

If little data is databases and things not generally lumped into the big data bucket, and if you think or perceive big data only to be Hadoop map reduce based data, then does that mean all the large unstructured non little data is then very big data or VBD?

StorageIO industry trends cloud, virtualization and big data

Of course the virtualization folks might want to if they have not already corner the V for Virtual Big Data. In that case, then instead of Very Big Data, how about very very Big Data (vvBD). How about Ultra-Large Big Data (ULBD), or High-Revenue Big Data (HRBD), granted the HR might cause some to think its unique for Health Records, or Human Resources, both btw leverage different forms of big data regardless of what you see or think big data is.

Does that then mean we should really be calling videos, audio, PACs, seismic, security surveillance video and related data to be VBD? Would this further confuse the market, or the industry or help elevate it to a grander status in terms of size (data file or object capacity, bandwidth, market size and application usage, market revenue and so forth)?

Do we need various industry consortiums, lobbyists or trade groups to go off and create models, taxonomies, standards and dictionaries based on their constituents needs and would they align with those of the customers, after all, there are big dollars flowing around big data industry adoption (marketing).

StorageIO industry trends cloud, virtualization and big data

What does this all mean?

Is Big Data BS?

First let me be clear, big data is not BS, however there is a lot of BS marketing BS by some along with hype and fud adding to the confusion and chaos, perhaps even missed opportunities. Keep in mind that in chaos and confusion there can be opportunity for some.

IMHO big data is real.

There are different variations, use cases and types of products, technologies and services that fall under the big data umbrella. That does not mean everything can or should fall under the big data umbrella as there is also little data.

What this all means is that there are different types of applications for various industries that have big and little data, virtual and very big data from videos, photos, images, audio, documents and more.

Big data is a big buzzword bingo term these days with vendor marketing big dollars being applied so no surprise the buzz, hype, fud and more.

Ok, nuff said, for now...

Cheers Gs

Greg Schulz - Author Cloud and Virtual Data Storage Networking (CRC Press, 2011), The Green and Virtual Data Center (CRC Press, 2009), and Resilient Storage Networks (Elsevier, 2004)

twitter @storageio

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2012 StorageIO All Rights Reserved

Read the original blog entry...

About Greg Schulz
Greg Schulz is founder of the Server and StorageIO (StorageIO) Group, an IT industry analyst and consultancy firm. Greg has worked with various server operating systems along with storage and networking software tools, hardware and services. Greg has worked as a programmer, systems administrator, disaster recovery consultant, and storage and capacity planner for various IT organizations. He has worked for various vendors before joining an industry analyst firm and later forming StorageIO.

In addition to his analyst and consulting research duties, Schulz has published over a thousand articles, tips, reports and white papers and is a sought after popular speaker at events around the world. Greg is also author of the books Resilient Storage Network (Elsevier) and The Green and Virtual Data Center (CRC). His blog is at www.storageioblog.com and he can also be found on twitter @storageio.

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Cloud Expo - Cloud Looms Large on SYS-CON.TV


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With our launch at Cloud Expo, we successfully transformed the company from a relatively unknown European player into the dominant player in the market. Our competitors were taken by surprise and just blown away. We got a huge number of really high quality leads..."
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@CloudExpo Blogs
One of the ways to increase scalability of services – and applications – is to go “stateless.” The reasons for this are many, but in general by eliminating the mapping between a single client and a single app or service instance you eliminate the need for resources to manage state in the app (overhead) and improve the distributability (I can make up words if I want) of requests across a pool of instances. The latter occurs because sessions don’t need to hang out and consume resources that could be used to serve other requests. Distribution should, in theory, be more even and enable better pred...
It’s time to talk more vociferously about open data. A better headline for this piece would be: why open data is not an overnight sensation or indeed a turn of a dial or a flick of a switch, i.e., it is not something automatically achieved without some kind of longer term strategic drive, which, in itself, typically needs to be driven by a defined longer term strategic need.
Business and IT leaders today need better application delivery capabilities to support critical new innovation. But how often do you hear objections to improving application delivery like, "I can harden it against attack, but not on this timeline"; "I can make it better, but it will cost more"; "I can deliver faster, but not with these specs"; or "I can stay strong on cost control, but quality will suffer"? In the new application economy, these tradeoffs are no longer acceptable. Customers will abandon your brand forever for a slow response or a privacy breach; competitors will steal critical ...
What we really mean to ask is whether microservices architecture is SOA done right. But then, of course, we’d have to figure out what microservices architecture was. And if you think defining SOA is difficult, pinning down microservices architecture is unquestionably frying pan into fire time. Given my years at ZapThink, fighting to help architects understand what Service-Oriented Architecture really was and how to get it right, it’s no surprise that many people ask me this question.
Unbeknownst to some, organizations have run infrastructure containers in production for years, reaping benefits on the operational end but not yet providing value for developers. When Docker catapulted containers into mainstream adoption, another type of container emerged — one that’s enormously popular for developers, but not quite ready for Ops. It’s time to close the gap between the promise that Devs see in containers and the operational challenges of actually running them in production. In his session at DevOps Summit, Bryan Cantrill, CTO at Joyent, will demonstrate a third path: contain...
Business Cloud News recently tied up with Sharp Document Solutions to interview more than 715 enterprise IT professionals from across the world for their study on cloud based collaboration. The objective of the study was to look at the level of proliferation of cloud tools in the enterprise setup of today and also to understand the factors that may be challenging this unbridled growth.
As organizations realize the scope of the Internet of Things, gaining key insights from Big Data, through the use of advanced analytics, becomes more crucial. Storage solutions that seamlessly integrate with robust data analytics platforms and act as “smart systems” provide in-place analytics that speed discovery and enable businesses to quickly derive meaningful and actionable insights. In his session at @ThingsExpo, Paul Turner, Chief Marketing Officer at Cloudian, will use specific use cases to address how and where we’ll see smart data first make an impact, and present the many benefits ...
Tableau Software and big data analytics platforms come together to provide visualization benefits for those seeking more than just crunched numbers. The next BriefingsDirect big data innovation discussion highlights how Tableau Software and big data analytics platforms come together to provide visualization benefits for those seeking more than just crunched numbers. They're looking for ways to improve their businesses effectively and productively, and to share the analysis quickly and broadly.
User expectations and rethinking of business productivity are having a profound impact on how business applications are used, designed, and leveraged to help buyers, sellers, and employees do their jobs better.
The Internet of Things. Cloud. Big Data. Real-Time Analytics. To those who do not quite understand what these phrases mean (and let’s be honest, that’s likely to be a large portion of the world), words like “IoT” and “Big Data” are just buzzwords. The truth is, the Internet of Things encompasses much more than jargon and predictions of connected devices. According to Parker Trewin, Senior Director of Content and Communications of Aria Systems, “IoT is big news because it ups the ante: Reach out and touch somebody is becoming reach out and touch everything.” In my previous blog, we talked about...
Cloud Migration Management (CMM) refers to the best practices for planning and managing migration of IT systems from a legacy platform to a Cloud Provider through a combination professional services consulting and software tools. A Cloud migration project can be a relatively simple exercise, where applications are migrated ‘as is’, to gain benefits such as elastic capacity and utility pricing, but without making any changes to the application architecture, software development methods or business processes it is used for.
Access is everything. It is the fundamental pillar that determines whether critical enterprise assets are safe or exposed. Knowing the answers to the questions of who is accessing what, where they are accessing that information from, why they are accessing that information and, finally, what exactly they’re accessing are the basic questions that stand between a breach and brand reputation.
"Actifio is essentially a software platform that can capture pretty much any data other than mainframe data and then allow customers to manage that data in its native form," explained Brian Reagan, Managing Director of Blackthorne Consulting Group, an Actifio company, in this SYS-CON.tv interview at DevOps Summit, held June 9-11, 2015, at the Javits Center in New York City.
With worldwide spending on cloud services and infrastructure growing by 23% in 2015 to $118B, it is clear that cloud services are here to stay. Yet, the rate of cloud adoption varies by companies and markets around the world. With thousands of outages and hijacks across the Internet every day, one reason for hesitation is the faith in quality Internet performance. In his session at 16th Cloud Expo, Michael Kane, Senior Manager at Dyn, explored how Internet performance affects your end-user’s experience and how you can make variations in the Internet work to your competitive advantage.
How do you securely enable access to your applications in AWS without exposing any attack surfaces? The answer is usually very complicated because application environments morph over time in response to growing requirements from your employee base, your partners and your customers. In his session at @DevOpsSummit, Haseeb Budhani, CEO and Co-founder of Soha, shared five common approaches that DevOps teams follow to secure access to applications deployed in AWS, Azure, etc., and the friction and risks they impose on the business.
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Past SYS-CON Events
    Cloud Expo West
cloudcomputingexpo
2011west.sys-con.com

 
    Cloud Expo East
cloudcexpo
2011east.sys-con.com

 
    Cloud Expo West
cloudcomputingexpo
2010west.sys-con.com

 
    Virtualization Expo West
virtualization
2010west.sys-con.com
    Cloud Expo Europe
cloudexpoeurope2010.
sys-con.com

 
    Cloud Expo East
cloudcomputingexpo
2010east.sys-con.com

 
    Virtualization Expo East
virtualizationconference
2010east.sys-con.com
    Cloud Expo West
cloudcomputingexpo
2009west.sys-con.com

 
    Virtualization Expo West
virtualizationconference
2009west.sys-con.com
    GovIT Expo
govitexpo.com
 
    Cloud Expo Europe
cloudexpoeurope2009.sys-con.com
 

Cloud Expo 2011 Allstar Conference Faculty

S.F.S.
Dell

Singer
NRO

Pereyra
Oracle

Ryan
OpSource

Butte
PwC

Leone
Oracle

Riley
AWS

Varia
AWS

Lye
Oracle

O'Connor
AppZero

Crandell
RightScale

Nucci
Dell Boomi

Hillier
CiRBA

Morrison
Layer 7 Tech

Robbins
NYT

Schwarz
Oracle

What The Enterprise IT World Says About Cloud Expo
 
"We had extremely positive feedback from both customers and prospects that attended the show and saw live demos of NaviSite's enterprise cloud based services."
  –William Toll
Sr. Director, Marketing & Strategic Alliances
Navisite
 


 
"More and better leads than ever expected! I have 4-6 follow ups personally."
  –Richard Wellner
Chief Scientist
Univa UD
 


 
"Good crowd, good questions. The event looked very successful."
  –Simon Crosby
CTO
Citrix Systems
 


 
"It's the largest cloud computing conference I've ever seen."
  –David Linthicum
CTO
Brick Group