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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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"delaPlex is a software development company. We do team-based outsourcing development," explained Mark Rivers, COO and Co-founder of delaPlex Software, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.

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Sponsorship opportunities are now open for Cloud Expo 2016 Silicon Valley, Nov. 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, and for Cloud Expo 2017 New York, June 6-8, 2017, at the Javits Center in New York City, New York.. For sponsorship, exhibit opportunities and show prospectus, please contact Carmen Gonzalez, carmen (at) sys-con.com.

Big Data Expo Silicon Valley All-Star Speakers Include

RICHARDS
Venafi

SINGH
IBM
Cloud Expo New York All-Star Speakers Include

DE MENO
Commvault

ERWAY
Appneta

OXENHORN
FalconStor

HINCH-
CLIFFE

7Summits

DOYLE
eCube

CHAVES
Pythian

BLOOMBERG
Intellyx

BUGAYENKO
Teamed.io

LAWSON
NewSci

HAFF
RedHat

HOLT
IBM

Jewell
Codenvy

MORGENTHAL
CSC

ARMSTRONG
AppNeta

DWYER
Iron.io

MATSUMURA
Gradle

WARFIELD
Coho

GRECO
Kaazing

PRESLEY
Pythian

LOVELL-TROY
Pythian

ATCHISON
New Relic

BHUSVANE-
SHWARI

Microsoft

GUCCIONE
Keeper

FLOREA
Tintri

KERBY
BMC

RAO
Asurion

BRENTON
CollabNet

SRINIVASAN
Symantec

GALBRAITH
HPE

NEWTON
Alfresco

ROGERS
Anexia

MORRISH
Interoute

TIFFANY
SoftLayer

OSTROVER-
KHYI

Mobidev

LEWIS
Formation
Data

KENDRICK
Isomorphic

REEVES
Datical

WALLER-
STORFER

Dynatrace

CIOT
Progress

MOR
Cloudyn

LEFORT
BMC

ANDERSON
BMC

BRODY
Webair

NIELSEN
Redis Labs

SEHGAL
Tintri

MANN
Splunk

YOO
Fuze

COTY
Alert Logic

LANDA
Kintone

CHOQUETTE
RackN

MARTIN
Security

HURWITZ
Hurwitz & Assc.

Cloud Expo Silicon Valley All-Star Speakers Include

KOWALL
AppDynamics

VAN TUIN
Red Hat

DEMMER
Jut

COHEN
Netflix

MUCHANDI
Red Hat Inc

BORELLO
Sysdig

GILPIN
Conjur

KANADE
Harbinger
Systems

GORBACHEV
Systems
Services Inc.

SUSSMAN
Coalfire

KHAN
Solgeniakhela

CHOKSI
Harbinger
Systems

DE MENO
CommVault

BLOOMBERG
Intellyx

BUGWADIA
Nirmata

COTY
Alert Logic

FLETCHER
Alert Logic

CAUTHRON
NIMBOXX

LYNN
AgilData

WAGNER
Cloudyn

ANAND
Appocito

WEISS
Pythian

BRODY
Webair

JACKSON
Softlayer

DAVIDSON
Juniper

HOFFMAN
Pivotal

VERVAET
HGST

Murthy
CloudRaxak

FRANCISCO
Evolute

LETCHIN
Nexenta

SIMON
JFrog

BONIFAZI
Solgenia

WEISS
ProfitBricks

HOLT
IBM

HANNON
SoftLayer

GALLO
SoftLayer

SAYEGH
Codero

BIMMU
Clouber

SRINIVAS
IBM

CHAVAN
IBM

HEDGES
Clouddata

AHUJA
Cloud

MEINER
Oracle

SWARTZ
Ericsson
Cloud Expo New York All-Star Speakers Included

DE SOUZA
Cisco

POTTER
SafeLogic

ROBINSON
CompTIA

WARUSA
-WITHANA

WSO2 Inc

MEINER
Oracle

CHOU
Microsoft

HARRISON
Tufin

BRUNOZZI
VMware

KIM
MapR

KANE
Dyn

SICULAR
Basho

TURNER
Cloudian

KUMAR
Liaison

ADAMIAK
Liaison

KHAN
Solgenia

BONIFAZI
Solgenia

SUSSMAN
Coalfire

ISAACSON
RMS

LYNN
CodeFutures

HEABERLIN
Windstream

RAMA
MURTHY

Virtusa

BOSTOCK
IndependenceIT

DE MENO
CommVault

GRILLI
Adobe

WILLIAMS
Rancher Labs

CRISWELL
Alert Logic

COTY
Alert Logic

JACOBS
SingleHop

MARAVEI
Cisco

JACKSON
Softlayer

SINGH
IBM

HAZARD
Softlayer

GALLO
Softlayer

TAMASKAR
GENBAND

SUBRA
-MANIAN

Emcien

LEVESQUE
Windstream

IVANOV
StorPool

BLOOMBERG
Intellyx

BUDHANI
Soha

HATHAWAY
IBM Watson

TOLL
ProfitBricks

LANDRY
Microsoft

BEARFIELD
Blue Box

HERITAGE
Akana

PILUSO
SIASMSP

HOLT
IBM Cloudant

SHAN
CTS

PICCININNI
EMC

BRON-
GERSMA

Modulus

PAIGE
CenturyLink

SABHIKHI
Cognitive Scale

MILLS
Green House Data

KATZEN
CenturyLink

SLOPER
CenturyLink

SRINIVAS
EMC

TALREJA
Cisco

GORBACHEV
Systems Services Inc.

COLLISON
Apcera

PRABHU
OpenCrowd

LYNN
CodeFutures

SWARTZ
Ericsson

MOSHENKO
CoreOS

BERMINGHAM
SIOS

WILLIS
Stateless Networks

MURPHY
Gridstore

KHABE
Vicom

NIKOLOV
GetClouder

DIETZE
Windstream

DALRYMPLE
EnterpriseDB

MAZZUCCO
TierPoint

RIVERA
WHOA.com

HERITAGE
Akana

SEYMOUR
6fusion

GIANNETTO
Author

CARTER
IBM

ROGERS
Virtustream
Cloud Expo Silicon Valley All-Star Speakers

TESAR
Microsoft

MICKOS
HP

BHARGAVA
Intel

RILEY
Riverbed

DEVINE
IBM

ISAACSON
CodeFutures

LYNN
HP

HINKLE
Citrix

KHAN
Solgenia

SINGH
Bigdata

BEACH
SendGrid

BOSTOCK
IndependenceIT

DE SOUZA
Cisco

PATTATHIL
Harbinger

O'BRIEN
Aria Systems

BONIFAZI
Solgenia

BIANCO
Solgenia

PROCTOR
NuoDB

DUGGAL
EnterpriseWeb

TEGETHOFF
Appcore

BRUNOZZI
VMware

HICKENS
Parasoft

KLEBANOV
Cisco

PETERS
Esri

GOLDBERG
Vormetric

CUMBER-
LAND

Dimension

ROSENDAHL
Quantum

LOOMIS
Cloudant

BRUNO
StackIQ

HANNON
SoftLayer

JACKSON
SoftLayer

HOCH
Virtustream

KAPADIA
Seagate

PAQUIN
OnLive

TSAI
Innodisk

BARRALL
Connected Data

SHIAH
AgilePoint

SEGIL
Verizon

PODURI
Citrix

COWIE
Dyn

RITTEN-
HOUSE

Cisco

FALLOWS
Kaazing

THYKATTIL
TimeWarner

LEIDUCK
SAP

LYNN
HP

WAGSTAFF
BSQUARE

POLLACK
AOL

KAMARAJU
Vormetric

BARRY
Catbird

MENDEN-
HALL

SUPERNAP

SHAN
KEANE

PLESE
Verizon

BARNUM
Voxox

TURNER
Cloudian

CALDERON
Advanced Systems

AGARWAL
SOA Software

LEE
Quantum

OBEROI
Concurrent, Inc.

HATEM
Verizon

GALEY
Autodesk

CAUTHRON
NIMBOXX

BARSOUM
IBM

GORDON
1Plug

LEWIS
Verizon

YEO
OrionVM

NAKAGAWA
Transparent Cloud Computing

SHIBATA
Transparent Cloud Computing

NATH
GE

GOKCEN
GE

STOICA
Databricks

TANKEL
Pivotal Software

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Testimonials
This week I had the pleasure of delivering the opening keynote at Cloud Expo New York. It was amazing to be back in the great city of New York with thousands of cloud enthusiasts eager to learn about the next step on their journey to embracing a cloud-first worldl."
@SteveMar_Msft
General Manager of Window Azure
 
How does Cloud Expo do it every year? Another INCREDIBLE show - our heads are spinning - so fun and informative."
@SOASoftwareInc
 
Thank you @ThingsExpo for such a great event. All of the people we met over the past three days makes us confident IoT has a bright future."
Yasser Khan
CEO of @Cnnct2me
 
One of the best conferences we have attended in a while. Great job, Cloud Expo team! Keep it going."

@Peak_Ten


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Business Executives including CEOs, CMOs, & CIOs , Presidents & SVPs, Directors of Business Development , Directors of IT Operations, Product and Purchasing Managers, IT Managers.

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@CloudExpo Blogs
Information security has become a critical priority for many businesses over the past decade, and for good reason. It seems like a new breach is exposed on nearly a daily basis, impacting another organization and its patrons. However, some companies believe that they're safe because they're either too small or too big to be affected by any of these cyberattacks. The truth is that groups of all sizes from Target to your local dentist are being hacked or having their data compromised, and it's causing a major upheaval in the security community.
Karen Field, Penton Communications' IoT Institute director, in her article "Start Small to Gain Big," postulated an oil drilling platform with 30,000 sensors would generate about 1 Terabyte of data per day. She also stressed that only 1% of that data would likely be used. From a systems engineering point of view this data flow is multiplied by the trillions of other IoT sensors in the cloud, introducing unprecedented data processing and data transport stress. Industries and competing companies within those industries will also be forced to weigh the economic impact of paying for this transport...
xMatters for the Enterprise DevOps toolchain stitches together the disparate operational tools to help orchestrate hand-offs between the tools and team members. Customers like us because we understand the need for DevOps or NoOps automation at enterprise scale and recognize that humans are still involved when something goes wrong.
The cloud promises new levels of agility and cost-savings for Big Data, data warehousing and analytics. But it’s challenging to understand all the options – from IaaS and PaaS to newer services like HaaS (Hadoop as a Service) and BDaaS (Big Data as a Service). In her session at @BigDataExpo at @ThingsExpo, Hannah Smalltree, a director at Cazena, provided an educational overview of emerging “as-a-service” options for Big Data in the cloud. This is critical background for IT and data professionals, as experts estimate that “as-a-service” cloud sourcing will increase from today’s 15% to 35% by...
In the world of DevOps there are ‘known good practices’ – aka ‘patterns’ – and ‘known bad practices’ – aka ‘anti-patterns.' Many of these patterns and anti-patterns have been developed from real world experience, especially by the early adopters of DevOps theory; but many are more feasible in theory than in practice, especially for more recent entrants to the DevOps scene. In this power panel at @DevOpsSummit at 18th Cloud Expo, moderated by DevOps Conference Chair Andi Mann, panelists discussed the patterns and anti-patterns of DevOps, and what it means to ‘do the right thing’ in a DevOps wa...
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, which can process our conversational commands and orchestrate the outcomes we request across our perso...
Security is one of the most controversial topics in the software industry. How do you measure security? Is your favorite software fundamentally insecure? Are Docker containers secure? Dan Walsh, SELinux architect, wrote: "Some people make the mistake of thinking of containers as a better and faster way of running virtual machines. From a security point of view, containers are much weaker." Meanwhile, James Bottomley, Linux Maintainer and former Parallels CTO, wrote: "There's contentions all over the place that containers are not actually as secure as hypervisors. This is not really true. Para...
Too many myths and hypes create the confusion around digital transformation. Digital transformation isn't a technology change matter, it's primarily about transforming business models: infrastructure and operating model. Digital transformation when tackled with proven methodologies and approaches isn't as complex as it seems, they provide the step-by-step guide, the logic, and the tools to make it easy.
One of the greatest challenges facing business and government organizations is how to store and move sensitive data around the world while maintaining security. Storing and securing critical data held within data centers (whether physical or virtual) is top of mind from the boardroom to the remote data center. According to the International Data Corporation (IDC) Worldwide Quarterly Cloud IT Infrastructure Tracker, spending on private cloud IT infrastructure in 2015 will grow by 15.8 percent year over year to $12.1 billion, while spending on public cloud IT infrastructure will increase by 29.6...
IDC estimates that the digital universe is doubling every two years. That means the need for data storage is increasing at the same rate. This exponential demand is no match for traditional vertical-scaling storage architectures. The resulting bottlenecks significantly reduce performance, and trying to store so much data would require prohibitively expensive server scale-out.
Big Data automation can mean writing dozens of scripts to process different input sources and aligning them in order to consolidate all this data and produce the required output. Why exactly do you need Big Data for your enterprise projects? Many industry observers have been noting that although a lot of enterprises like to claim that their big data projects are aimed at "deriving insights" that replace human intuition with data-driven alternatives, in reality though, the objective appears to be automation. They point out that the role of data scientists at a lot of organizations has got litt...
Cloud Expo 2016 New York at the Javits Center New York was characterized by increased attendance and a new focus on operations. These were both encouraging signs for all involved in Cloud Computing and all that it touches. As Conference Chair, I work with the Cloud Expo team to structure three keynotes, numerous general sessions, and more than 150 breakout sessions along 10 tracks. Our job is to balance the state of enterprise IT today with the trends that will be commonplace tomorrow. Mobile Computing, Big Data and Analytics, the Internet of Things, Platforms and Microservices and Containe...
Fog Computing is being touted as the data communication solution our Internet of Things (IoT) devices are asking for by bringing the power of cloud computing closer to the end user. The fact is, the number of connected devices is going to continue to grow exponentionally. In fact, Gartner predicts that by 2020 IoT will include 26 billion connected things. Consider the impact that amount of data collected and processed will have.
Advances in thin clients, desktop virtualization (VDI), cloud management services, and mobile delivery networks are allowing both increased security and edge applications performance gains. The next BriefingsDirect thought leadership panel discussion focuses on the heightened role of security in the age of global cloud and mobile delivery of apps and data. As enterprises and small to medium-sized businesses (SMBs) alike weigh the balance of apps and convenience with security -- a new dynamic is emerging. Security concerns increasingly dwarf other architecture considerations. Yet advances ...
IoT networking requirements are vastly different from those supported by today's cloud network. The processing and transport levels are multiple orders of magnitude higher than ever seen before. More importantly though, societal economic and the safety ramifications of making mistakes during this transition are off the scale. This is why system engineering of the cloud computing network is now an immediate global imperative.