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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.

Presentation Slides
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With microservices, SOA and distributed architectures becoming more popular, it is becoming increasingly harder to keep track of where time is spent in a distributed application when trying to diagnose performance problems. Distributed tracing systems attempt to address this problem by following application requests across service boundaries, persisting metadata along the way that provide context for fine-grained performance monitoring.
WebRTC has had a real tough three or four years, and so have those working with it. Only a few short years ago, the development world were excited about WebRTC and proclaiming how awesome it was. You might have played with the technology a couple of years ago, only to find the extra infrastructure requirements were painful to implement and poorly documented. This probably left a bitter taste in your mouth, especially when things went wrong.
DevOps has often been described in terms of CAMS: Culture, Automation, Measuring, Sharing. While we’ve seen a lot of focus on the “A” and even on the “M”, there are very few examples of why the “C" is equally important in the DevOps equation. In her session at @DevOps Summit, Lori MacVittie, of F5 Networks, explored HTTP/1 and HTTP/2 along with Microservices to illustrate why a collaborative culture between Dev, Ops, and the Network is critical to ensuring success.
The modern software development landscape consists of best practices and tools that allow teams to deliver software in a near-continuous manner. By adopting a culture of automation, measurement and sharing, the time to ship code has been greatly reduced, allowing for shorter release cycles and quicker feedback from customers and users. Still, with all of these tools and methods, how can teams stay on top of what is taking place across their infrastructure and codebase? Hopping between services a...
Learn how IoT, cloud, social networks and last but not least, humans, can be integrated into a seamless integration of cooperative organisms both cybernetic and biological. This has been enabled by recent advances in IoT device capabilities, messaging frameworks, presence and collaboration services, where devices can share information and make independent and human assisted decisions based upon social status from other entities. In his session at @ThingsExpo, Michael Heydt, founder of Seamless...
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The IoT's basic concept of collecting data from as many sources possible to drive better decision making, create process innovation and realize additional revenue has been in use at large enterprises with deep pockets for decades. So what has changed? In his session at @ThingsExpo, Prasanna Sivaramakrishnan, Solutions Architect at Red Hat, discussed the impact commodity hardware, ubiquitous connectivity, and innovations in open source software are having on the connected universe of people, thi...
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For it to be SOA – let alone SOA done right – we need to pin down just what "SOA done wrong" might be. First-generation SOA with Web Services and ESBs, perhaps? But then there's second-generation, REST-based SOA. More lightweight and cloud-friendly, but many REST-based SOA practices predate the microservices wave. Today, microservices and containers go hand in hand – only the details of "container-oriented architecture" are largely on the drawing board – and are not likely to look much like S...
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Everyone talks about continuous integration and continuous delivery but those are just two ends of the pipeline. In the middle of DevOps is continuous testing (CT), and many organizations are struggling to implement continuous testing effectively. After all, without continuous testing there is no delivery. And Lab-As-A-Service (LaaS) enhances the CT with dynamic on-demand self-serve test topologies. CT together with LAAS make a powerful combination that perfectly serves complex software developm...
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Join us at Cloud Expo | @ThingsExpo 2016 – June 7-9 at the Javits Center in New York City and November 1-3 at the Santa Clara Convention Center in Santa Clara, CA – and deliver your unique message in a way that is striking and unforgettable by taking advantage of SYS-CON's unmatched high-impact, result-driven event / media packages.
At first adopted by enterprises to consolidate physical servers, virtualization is now widely used in cloud computing to offer elasticity and scalability. On the other hand, Docker has developed a new way to handle Linux containers, inspired by version control software such as Git, which allows you to keep all development versions. In his session at 17th Cloud Expo, Dominique Rodrigues, the co-founder and CTO of Nanocloud Software, discussed how in order to also handle QEMU / KVM virtual machin...
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OXENHORN
FalconStor

HURWITZ
Hurwitz & Assc.

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

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
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DE MENO
CommVault

BLOOMBERG
Intellyx

BUGWADIA
Nirmata

COTY
Alert Logic

FLETCHER
Alert Logic

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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

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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

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Cisco

PETERS
Esri

GOLDBERG
Vormetric

CUMBER-
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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

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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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@CloudExpo Blogs
Here in the US, the Super Bowl is more than just a football game - it's a national holiday, with its own traditions, festivities, and food and drinks. One of the most important aspects of super bowl is the commercials. Every year, brands spend millions of dollars to get the attention of the more than 120 million Super Bowl viewers. The Wall Street Journal created this brilliant interactive chart of past ad spending. We are sure that the all industries outdid themselves in terms of spending again this year.
Adding public cloud resources to an existing application can be a daunting process. The tools that you currently use to manage the software and hardware outside the cloud aren’t always the best tools to efficiently grow into the cloud. All of the major configuration management tools have cloud orchestration plugins that can be leveraged, but there are also cloud-native tools that can dramatically improve the efficiency of managing your application lifecycle. In his session at 18th Cloud Expo, Alex Lovell-Troy, Director of Solutions Engineering at Pythian, will present a roadmap that can be l...
With some of the busiest shopping days of the year behind us, now is the time for retailers to pause for a moment to evaluate what worked, and to consider new online strategies and technologies for the 2016 shopping season. We don’t yet have numbers for 2015, but in 2014, holiday season retail e-commerce spending in the United States amounted to 53.3 billion U.S. dollars with the most money being spent online on Cyber Monday. Fujitsu is working with Grid Dynamics to deliver an Oracle Commerce Platform as a fully-managed cloud service. I had a chance to sit down with Victoria Livschitz, E...
At first adopted by enterprises to consolidate physical servers, virtualization is now widely used in cloud computing to offer elasticity and scalability. On the other hand, Docker has developed a new way to handle Linux containers, inspired by version control software such as Git, which allows you to keep all development versions. In his session at 17th Cloud Expo, Dominique Rodrigues, the co-founder and CTO of Nanocloud Software, discussed how in order to also handle QEMU / KVM virtual machines versions, they have developed a new tool, called Vm_commit, which can create commits, backup any ...
Microservices are all the rage right now — and the industry is still learning, experimenting, and developing patterns, for successfully designing, deploying and managing Microservices in the real world. Are you considering jumping on the Microservices-wagon? Do Microservices make sense for your particular use case? What are some of the “gotchas” you should be aware of? This morning on #c9d9 we had experts from popular chat app Kik, SMB SaaS platform Yodle and hosted CI solution Semaphore share their journey and learnings from decomposing their monolithic application into Microservices. Wit...
If we look at slow, traditional IT and jump to the conclusion that just because we found its issues intractable before, that necessarily means we will again, then it’s time for a rethink. As a matter of fact, the world of IT has changed over the last ten years or so. We’ve been experiencing unprecedented innovation across the board – innovation in technology as well as in how people organize and accomplish tasks. Let’s take a look at three differences between today’s modern, digital context for enterprise IT as compared to conventional wisdom – wisdom that may have applied only a handful ...
The (re?)emergence of Microservices was especially prominent in this week’s news. What are they good for? do they make sense for your application? should you take the plunge? and what do Microservices mean for your DevOps and Continuous Delivery efforts? Continue reading for more on Microservices, containers, DevOps culture, and more top news from the past week. As always, stay tuned to all the news coming from@ElectricCloud on DevOps and Continuous Delivery throughout the week and retweet/favorite to get your favorite pieces featured in our weekly recap.
Over the past year, Microsoft has been introducing Azure Resource Manager (ARM) as the preferred way to provision and manage resources in its Azure cloud. ARM is the successor to the original Service Management model, also known as “Classic.”[1] While Classic will continue to be supported for the foreseeable future, ARM is the preferred deployment model and all new Azure features are being released on ARM only. Here is an overview ARM and the new features it provides.
In the middle of World War II, very basic and primitive computers were designed to improve accuracy for naval gunfire. The first computers ran complex mathematical applications to calculate trajectories and gunfire from large battleships. The size of the computer was huge and was made up of vacuum-tube technology. You could literally walk into the computer. (And needed to, when a tube went bad and you had to replace it.)
The Federal Government’s “Cloud First” policy mandates that agencies take full advantage of cloud computing benefits to maximize capacity utilization, improve IT flexibility and responsiveness, and minimize cost. The Federal Risk and Authorization Management Program (FedRAMP) is a mandatory government-wide program that provides a standardized approach to security assessment, authorization, and continuous monitoring for cloud products and services. Advantages for business include being able to market to many federal agencies after a single FedRAMP review following the government’s “approve once...
My colleague, Jennelle Crothers, and I got a chance to chat about the usability and ease of use in this episode of Windows 10 series in TechNet Radio. She’s great and we had much fun doing it. Jennelle did a quick demo on how to make Windows 10 even easier to use.
Teams that have embraced DevOps and begun using the practice of test driven development are familiar with the headaches that accompany testing legacy code. This is particularly true for companies that have applications out in production that have been working for years, but have no formal tests or testing regiment associated with its codebase. Most of the time the physical code for the applications is known; many times it is not. In fact, both the code and the developer who wrote the code might have left the building years ago.
With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right provider and with the proper expectations. In his session at 18th Cloud Expo, Warner Chaves, Princ...
I sat down with Michael Rösch, COO of POOL4TOOL, to chat about cloud computing. With a lot of buzz about the impact of the cloud on business, it was a chance to get a perspective, as well as a few hints and tips, from someone who has been at the coalface of procurement cloud services for the past 15 years. Michael has been at POOL4TOOL since 2000, becoming COO in 2012, and has worked on projects with German giants like Behr, Hansgrohe, Heidelberger Printing Presses, Carl Zeiss and ThyssenKrupp Presta in that time.
The arrival of the Microsoft Azure Stack Technical Preview marks a turning point in the cloud-computing market and forms a leading indicator of how dramatically Microsoft has changed in the past two years. The cloud turning point comes because the path to hybrid-cloud capabilities and benefits has a powerful new usher, one with the enterprise, developer, and service-provider presence, R and D budget, and competitive imperative to succeed in a market still underserved and nebulous.