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How Global Data Availability
Accelerates Collaboration
And Delivers Business Insights
A transcript of a discussion that explores how comprehensive and global data storage access
delivers the rapid insights businesses need for digital business transformation.
Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: IBM Storage.
Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions and
you’re listening to BriefingsDirect.
Our next data strategy insights discussion explores the payoffs when enterprises
overcome the hurdles of disjointed storage to obtain global data access.
By leveraging the latest in container and storage server technologies, the holy grail of
inclusive, comprehensive, and actionable storage can be obtained. And such access
extends across all deployment models – from hybrid cloud, to software-as-a-service
(SaaS), to distributed data centers, and edge.
Stay with us now as we examine the role that
comprehensive data storage plays in delivering
the rapid insights businesses need for digital
business transformation. To learn how, we’re
joined again by Denis Kennelly, General
Manager, IBM Storage. Welcome back, Denis.
Kennelly: Thank you, Dana.
Gardner: Denis, in our earlier discussions in this
three-part series we learned about IBM’s vision
for global consistent data, as well as the newest
systems forming the foundation for these
advances.
But let’s now explore the many value streams
gained from obtaining global data access. We
hear a lot about the rise of artificial intelligence (AI) adoption needed to support digital
businesses. So what role does a modern storage capability -- particularly with a global
access function and value -- play in that AI growth?
Kennelly: As enterprises become increasingly digitally transformed, the amount of data
they are generating is enormous. IDC predicts that something like 42 billion Internet of
Kennelly

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things (IoT) devices will be sold by 2025, and so the role of storage is not only
centralized to data centers. It needs to be distributed across this entire hybrid cloud
environment.
Discover, share, and analyze data with AI
For actionable AI, you want to build models on all of the data that’s been generated
across this environment. Being able to discover and understand that data is critical, and
that’s why it’s a key part of our storage capabilities. You need to run that storage on all
of these highly distributed environments in a seamless fashion. You could be running
anywhere -- the data center, the public cloud, and at edge locations. But you want to
have the same software and capabilities for all of these locations to allow for that
essential seamless access.
That’s critical to enabling an AI journey
because AI doesn’t just operate on the data
sitting in a public cloud or data center. It
needs to operate on all of the data if you want
to get the best insights. You must get to the
data from all of these locations and bring it
together in a seamless manner.
Gardner: When we’re able to attain such global availability of data -- particularly in a
consistent context – how does that accelerate AI adoption? Are there particular use
cases, perhaps around DevOps? How do people change their behavior when it comes to
AI adoption, thanks to what the storage and data consistency can do for them?
Kennelly: First it’s about knowing where the data is and doing basic discovery. And
that’s a non-trivial task because data is being generated across the enterprise. We are
increasingly collaborating remotely and that generates a lot of extended data. Being able
to access and share that data across environments is a critical requirement. It’s
something that’s very important to us.
Then -- as you discover and share the data – you can also bring that data together into
use by AI models. You can use it to actually generate better AI models across the
various tiers of storage. But you don’t want to just end up saying, “Okay, I discovered all
of the data. I’m going to move it to this certain location and then I’m going to run my
analytics on it.”
Instead, you want to do the analytics in real time and in a distributed fashion. And that’s
what’s critical about the next level of storage.
Coming back to what’s hindering AI adoption, number one is that data discovery
because enterprises spent a huge amount of time just discovering the data. And when
you get access, you need to have seamless access. And then, of course, as you build
AI doesn’t just operate on the
data center sitting in a public
cloud or data center. … You
must get to the data from all of
these locations and bring it
together in a seamless manner.

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your AI models you need to infuse those analytics into the applications and capabilities
that you’re developing.
And that leads to your question around DevOps, to be able to integrate the processes of
generating and building AI models into the application development process so that we
make sure the application developers can leverage those insights for the applications
they are building.
Gardner: For many organizations, moving to hybrid cloud has been about application
portability. But when it comes to the additional data mobility we gain from consistent
global data access, there’s a potential greater value. Is there a second shoe to fall, if you
will, Denis, when we can apply such data mobility in a hybrid cloud environment?
Essential to access data across hybrid cloud
Kennelly: Yes, and that second shoe is about to fall. The first part of our collective
cloud journey was all about moving to the public cloud, moving everything to public
clouds, and building applications with cloud-based data.
What we discovered in doing that is that life is not so simple, and we’re really now in a
hybrid cloud world for many reasons. Because of that success, we now need the hybrid
cloud approach.
That need for more cloud portability has led to technologies like containers to get
portability across all of these environments – from data centers to clouds. As we roll out
containers and these workloads into production, the whole data question is more critical.
You can now build an application that runs in a certain environment, and containers
allow you to move that application to other environments very quickly. But if the data
doesn’t follow -- if the data access doesn’t follow that application seamlessly -- then you
face some serious challenges and problems.
And that is the next shoe to drop, and
it’s dropping right now. As we roll out
these sophisticated applications into
production, being able to copy data or
get access to data across this hybrid
cloud environment is the biggest
challenge the industry is facing.
Gardner: When we envision such expansive data mobility, we often think about location,
but it also impacts the type of data – be it file, block, and object storage, for example.
Why must there be global access geographically -- but also in terms of the storage type
and across the underlying technology platforms?
As we roll out these sophisticated
applications into production, being able to
copy data or get access to data across
this hybrid cloud environment is the
biggest challenge the industry is facing.

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Kennelly: To the application developer, we really have to hide from them that layer of
complexity of the storage type and platform. At the end of the day, the application
developer is looking for a consistent API through which to access the data services,
whether that’s file, block, or object. They shouldn’t have to care about that level of detail.
It’s important that there’s a focus on consistent access via APIs to the developer. And
then the storage subsystem has to take care of the federated global access of the data.
Also, as we generate data, the storage subsystem should scale horizontally.
These are the design principles we have put into the IBM Storage platform. Number one,
you get seamless actions and consistent access – be it file, object, or block storage. And
we can scale horizontally as you generate data across that hybrid cloud environment.
Gardner: The good news is that global data access enablement can now be done with
greater ease. The bad news is the global access enablement can be done anywhere,
anytime, and with ease.
And so we have to also worry about access, security, permissions, and regulatory
compliance issues. How do you open the floodgates, in a sense, for common access to
distributed data, but at the same time put in the guardrails that allow for the management
of that access in a responsible way?
Global data access opens door to security risks
Kennelly: That’s a great question. As we introduce simplicity and ease of data access,
we can’t just open it up to everybody. We have to make sure we have good
authentication as part of the design, using things like two-factor authentication on the
data-access APIs.
But that’s only half of the problem. In the security world, the unfortunate acceptance is
that you probably are going to get breached. It’s in how you respond that really
differentiates you and determines how quickly you can get the business back on its feet.
And so, when something bad
happens, the third critical role for the
storage subsystem to play is in the
access control to the persistence
storage. At the end of the day, that
is what people are after. Being able
to understand the typical behavior of
those storage systems, and how
data is usually being stored, forms a baseline against which you can understand when
something out of the ordinary is happening.
Clearly, if you’re under a malware or CryptoLocker attack, you see a very different
input/output (IO) pattern than you would normally see. We can detect that in real time,
Being able to understand the typical
behavior of those storage systems, and
how data is usually stored, forms a
baseline against which you can
understand when something out of the
ordinary is happening.

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understand when it happens, and make sure you have protected copies of the data so
you can quickly access that and get back to business and back online quickly.
Why is all of that important? Because we live in a world where it’s not a case of if it will
happen, it’s really when it will happen. How we can respond is critical.
Gardner: Denis, throughout our three-part series we’ve been discussing what we can
do, but we haven’t necessarily delved into specific use cases. I know you can’t always
name businesses and reference customers, but how can we better understand the
benefits of a global data access capability in the context of use cases?
In practice, when the rubber hits the road, how does global data storage access enable
business transformation? Is there a key metric you look for to show how well your
storage systems support business outcomes?
Measures of global data storage access success
Kennelly: We’re at a point right now when customers are looking to drive new business
models and to move much more quickly in their hybrid cloud environments.
There are enabling technologies right now facilitating that. There’s a lot of talk about
edge with the advent of 5G networks, which enable a lot of this to happen. When you
talk about seamless access and the capability to distribute data across these
environments, you need the underlying network infrastructure to make that happen.
As we do that, we’re looking at a number of key business measures and metrics. We
have done some independent surveys and analysis looking at the business value that
we drive for our clients with a hybrid cloud platform and things like portability, agility, and
seamless data access.
In terms of business value, we
have four or five measures. For
example, we can drive roughly 2.5
times more business value for our
clients -- everything from top-line
growth to operational savings. And that’s something that we have tested with many
clients independently.
One example that’s very relevant in the world we live in today is we have a cloud
provider that needed to have more federated access to their global data. But they also
wanted to distribute that through edge nodes in a consistent manner. And that’s just an
example of why this is happening in action.
Gardner: You know, some of the major consumers of analytics in businesses these
days are data scientists, and they don’t always want to know what’s going on
underneath the covers. On the other hand, what goes on underneath the covers can
We can drive roughly 2.5 times more
business value for our clients – everything
from top-line growth to operational savings.

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greatly impact how well they can do their jobs, which are often essential to digital
business transformation.
For you to address a data scientist specifically about why global access for data and
storage modernization is key, what would you tell them? How do you describe the value
that you’re providing to someone like a data scientist who plays such a key role in
analytics?
Kennelly: Well, data scientists talk a lot about data sets. They want access to data sets
so they can test their hypothesis very quickly. In a nutshell, we surface data sets quicker
and faster than anybody else at a price performance that leads the industry -- and that’s
what we do every day to enable data scientists.
Gardner: Throughout our series of three storage strategy discussions, we’ve talked
about how we got here and what we’re doing. But we haven’t yet talked about what
comes next.
These enabling technologies not only satisfy business imperatives and requirements
now but set up organizations to be even more intelligent over time. Let’s look to the
future for the expanding values when you do data access globally and across hybrid
clouds well.
Insight-filled future drives business growth
Kennelly: Yes, you get to critically look at current and new business models. At the end
of the day, this is about driving business growth. As you start to look at these
environments -- and we’ve talked a lot about analytics and data – it becomes about
getting competitive advantage through real-time insights about what’s going on in your
environments.
You become able to better understand your supply chain, what’s happening in certain
products, and in certain manufacturing lines. You’re able to respond accordingly. There’s
a big operational benefit in terms of savings. You don’t have to have excess capacity in
the environment.
Also, in seeking new business
opportunities, you will detect the
patterns needed to have insights you
hadn’t had before by doing analytics
and machine learning into what’s
critical in your systems and markets.
If you move your IT environment and
centralize everything in one cloud, for example, then that really hinders that progress.
By being able to do that with all of the data as it’s generated in real time, you get very
unique insights that provide competitive advantage.
In seeking new business opportunities, you
will detect the patterns needed to have
insights you hadn’t had before by doing
analytics and machine learning into what’s
critical in your systems and markets.

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Gardner: And lastly, why IBM? What sets you apart from the competition in the storage
market for obtaining these larger goals of distributed analytics, intelligence, and
competitiveness?
Kennelly: We have shown over the years that we have been at the forefront of many
transformations of businesses and industries. Going back to the electronic typewriter, if
we want to go back far enough, or now to our business-to-business (B2B) or business-
to-employee (B2E) models in the hybrid cloud -- IBM has helped businesses make these
transformations. That includes everything from storage to data and AI through to hybrid
cloud platforms, with Red Hat Enterprise Linux, and right out to our business service
consulting.
IBM has the end-to-end capabilities to make that all happen. It positions us as an ideal
partner who can do so much.
I love to talk about storage and the value of storage, and I spend a lot of time talking with
people in our business consulting group to understand the business transformations that
clients are trying to drive and the role that storage has in that. Likewise, with our data
science and data analytics teams that are enabling those technologies.
The combination of all of those capabilities
as one idea is a unique differentiator for us in
the industry. And it’s why we are developing
the leading edge capabilities, products, and
technology to enable the next digital
transformations.
Gardner: I’m afraid we’ll have to leave it there. You have been listening to a sponsored
BriefingsDirect discussion on the major payoffs when enterprises overcome the hurdles
of disjointed storage to obtain global data access.
And we’ve learned about the role and impact of a comprehensive and global data
storage model when delivering rapid insights for accomplishing digital business
transformation.
So please join me impacting our guest, Denis Kennelly, General Manager, IBM Storage.
Thank you so much, Denis.
Kennelly: Thank you, Dana.
Gardner: And thanks as well to our audience for joining these BriefingsDirect data
strategies insights discussions. Please look for the other two discussions in this series
on the IBM Storage vision, as well as the newest systems that form the foundation for
these advances.
We [IBM] are developing the
leading edge capabilities,
products, and technology to enable
the next digital transformations.

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I’m Dana Gardner, principal analyst at Interarbor Solutions, your host throughout the
series of IBM Storage sponsored BriefingsDirect discussions. Thanks again for listening.
Please pass this along to your IT community, and do come back next time.
Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: IBM Storage.
A transcript of a discussion that explores how comprehensive and global data storage access
delivers the rapid insights businesses need for digital business transformation. Copyright
Interarbor Solutions, LLC, 2005-2021. All rights reserved.
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