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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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There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Get a jump on that rapidly evolving trend at Big Data Expo, which we are introducing in June at
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@CloudExpo Blogs
Cloud Expo New York is happening from June 9 - 11. This event brings together the worlds of Cloud Computing, DevOps, IoT, WebRTC, Big Data and SDDC. We hope to see you there-members of the Blue Box team will exhibit in booth 218 next to the DevOps area. Plus, our Chief Product Officer, Hernan Alvarez, will present his talk "The Cloud Has a Down-and-Dirty Lining" as part of the Operations track in the DevOps Summit portion of the event on June 9 at 11 am. Learn more about his session here. To schedule time to meet one-to-one with Blue Box infrastructure experts, or to discuss partne...
DevOps has quickly become the buzzword du jour for the software industry and promotes something that many developers and IT Administrators don’t enjoy: collaboration. According to Wikipedia, “DevOps acknowledges the interdependence of software development, quality assurance, and IT operations“. By having all three arms of a technology department collaborating, software products and services can be produced with a high quality bar and operational efficiencies. In this article, we’ll review how IT operations can engage more with a customer’s experience and assist software development in isolatin...
Traditional storage was designed to present a LUN to a server. This worked well until that server became a hypervisor running 10, 20 or 30 virtual servers, all pointing to the same LUN. Adding to the complexity, all hypervisors need to point to the same LUN to enable VM mobility or high availability. Architecturally, this creates a many-to-one relationship that makes optimization impossible. Each VM has a different I/O pattern. When they all mix together, the aggregate I/O becomes highly random, creating performance issues with no way to isolate problems or control I/O per VM.
Docker is an open platform for developers and sysadmins of distributed applications that enables them to build, ship, and run any app anywhere. Docker allows applications to run on any platform irrespective of what tools were used to build it making it easy to distribute, test, and run software. I found this 5 Minute Docker video, which is very helpful when you want to get a quick and digestible overview. If you want to learn more, you can go to Docker’s web page and start with this Docker introduction video. Docker makes it very easy to make changes and package the software quickly for oth...
The last decade was about virtual machines, but the next one is about containers. Containers enable a service to run on any host at any time. Traditional tools are starting to show cracks because they were not designed for this level of application portability. Now is the time to look at new ways to deploy and manage applications at scale. In his session at 16th Cloud Expo, Jake Moshenko, Product Manager at CoreOS, will examine how CoreOS + Quay.io fit into the development lifecycle from pushing git changes all the way through to running in production. Attendees will understand how different ...
It is critical to let the usage of cloud collaboration grow over time instead of migration in a swoop. This will give your employees sufficient time to evolve while ensuring your company is on the right path forward. A recent study published by Markets and Markets predicts the collaboration tools market to more than double between now and 2018. In 2014, the market for collaboration software tools was valued at around $10.5 billion. By 2018, this market is expected to reach a size of more than $21 billion. That is a staggering compounded annual growth rate (CAGR) of 15%.
The 17th International Cloud Expo has announced that its Call for Papers is open. 17th International Cloud Expo, to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, APM, APIs, Microservices, Security, Big Data, Internet of Things, DevOps and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
Major product cycle changes tend to come around roughly every five years or so. The technology industry is fond of labeling these movements as paradigm shifts, but we’ve all heard too many of those things referenced, so let’s not go there. Looking back over the last decade and the emergence of touch, our appetite for richer controls is never long satisfied. As soon as one finger touch arrived we wanted two-finger touch. Pinch and zoom wasn’t far behind and multi-user touch soon followed.
There is no question that the cloud is where businesses want to host data. Until recently hypervisor virtualization was the most widely used method in cloud computing. Recently virtual containers have been gaining in popularity, and for good reason. In the debate between virtual machines and containers, the latter have been seen as the new kid on the block – and like other emerging technology have had some initial shortcomings. However, the container space has evolved drastically since coming onto the cloud hosting scene over 10 years ago. So, what has changed? In his session at 16th Cloud E...
One question I frequently get is: “How do I become a data scientist?” Wow, tough question. There are several new books that outline the different skills, capabilities and technologies that a data scientist is going to need to learn and eventually master. I’ve read several of these books and am impressed with the depth of the content. Unfortunately, these books spend the vast majority of their time reviewing and/or teaching things such as the data science processes (such as CRISP: Cross Industry Standard Process for Data Mining), and basic and advanced statistics, data mining and data visua...
One reason a lot of entrepreneurs flock to cloud-based services for their business is the cost. Native applications require licenses that are either too expensive or require elaborate set-up across all devices. In a recent article on the Entrepreneur, Bask Iyer, the CIO and Senior Vice President of Technology at Juniper Networks responded to the question, 'what entrepreneurs should put in the cloud?' His answer: "Everything." Bask elaborates by pointing out the ability of cloud to scale-up and scale-down at ease, the ease with which you can deploy plug-and-play cloud solutions for almost ever...
The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long development cycles that produce software that is obsolete at launch. DevOps may be disruptive, but it is essential. The DevOps Summit at Cloud Expo – to be held June 3-5, 2015, at the Javits Center in New York City – will expand the DevOps community, enable a wide sharing of knowledge, and educate delegates and technology providers alike. Recent research has sho...
The Internet of Things is already changing the way we track fitness, manage our homes, and drive our cars. But while there is considerable discussion around how we securely provision our devices and who will have access to the data they capture, an important topic no one seems to be talking much about is the de-provisioning of smart objects. What happens when I ditch my Fitbit, trade in my connected car, or sell my house with its Nest thermostat, smart fridge and next-generation home security system? How do I manage to remove these smart devices from my life and make sure that no one has acces...
Passing the Net Neutrality Act is not going to make us more competitive in the global marketplace. It is not going to give “the little guy” a better platform for a start-up business. It is not the answer. Net Neutrality has to somehow be forged into a more strategic initiative to build out the current network infrastructure with only two design constructs: It must be the fastest in the world and the most resilient in the world when it comes to reliability and redundancy built into its framework. Maybe Global Net Superiority (GNS) is more descriptive as to what we really need to facilitate. ...
How can you compare one technology or tool to its competitors? Usually, there is no objective comparison available. So how do you know which is better? Eclipse or IntelliJ IDEA? Java EE or Spring? C# or Java? All you can usually find is a holy war and biased comparisons on vendor sites. But luckily, sometimes, you can find a fair comparison. How does this come to be? By having it co-authored by the stakeholders. The binary repository comparison matrix is one of those rare resources. It is edited by JFrog, Sonatype and Archiva committers to provide you with an objective picture; every vendor a...
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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