Building an effective data approach in a hybrid cloud world

Building an effective data approach in a hybrid cloud world

“In today’s world of disruption and transformation, there are a few key things that all organizations are trying to figure out: how to remain relevant to their customer base, how to deal with the pressure of disruption in their industry and, undoubtedly, how to look to technology to help deliver a better service.”

Paul Mackay 

Today we are sitting down with Marc Beierschoder, Analytics & Cognitive Offering Lead at Deloitte Germany and Paul Mackay, the EMEA Cloud Lead at Cloudera to discuss the data challenges and opportunities for organizations as they strive to gain competitive advantage from technology innovation and disruption.

Thanks for joining us here today. Let’s kick off with a couple of open questions: How are organizations you’re talking to setting themselves apart from their competition? How important is technology’s role in delivering this advantage?


In each industry, technology is driving disruptive change, which in my opinion fuels competitive advantages. I see three factors affecting technology’s role in delivering competitive advantage:

  1. Technology itself is not the differentiator, but how that technology is used and embedded into existing processes, products, and services.
  2. Data privacy-preserving approaches, open-source, security, flexibility, interoperability, simplicity of the solution, and time-to-market currently play a significant role in the impact of technology for competitive differentiation.
  3. The focus of the business on the speed to adoption of technology-enabled innovation is adding a clear pressure onto the CIO and his team. Relevant skills may need to be developed to remain up-to-date.

Ultimately this combination of forces will lead to a technology-driven competitive advantage.


As well as running their mission-critical systems on which the business relies, the CIO also now needs to invest in these new technology trends. Currently, when a CIO looks at where their team is spending their time, in an ideal world they’d want the team to be spending most of their time on innovation and looking at new technologies. The reality is that most of that team’s resource (time, people, money) is being spent elsewhere – on legacy (but still vitally important) systems and simply keeping the lights on.

Source –

Take data and analytics as an example: how does the organization make a shift in balance to spend more time deriving value from data? Without this shift, they risk being in the weeds of managing systems that are trying to collect, filter, sort, and transform, which are of course essential, but ultimately taking time away from the work that needs to happen to actually get business value.

There’s no doubt there’s recognition that the organizations that will succeed in the future are those successfully leveraging new technologies and innovation going forward, not only transforming their business but transforming their workforce too.

So in the need to change mindsets from focusing not just on the tech, but also on the skilled workforce, what are some of the main ways that you see organizations pivot successfully?


Fast adoption of technology and re-training of the workforce is central to driving efficiencies (cost, people, time) and innovation from IT that businesses today demand. The re-training of the workforce needs a dedicated learning and upskilling strategy. In combination with agile working and the trend towards cloud, learning, and upskilling the workforce helps organizations to focus on innovation and business value. Innovation and change that took months before is now possible in days or even hours thanks to newfound agility and flexibility from technology. If the project doesn’t work, sunk costs are minimized since you only pay for what you actually use in cloud environments. That’s a game-changer for business and IT collaboration!

But cloud adoption comes with its own challenges. From the initial cloud setup and integration into the existing technology environment to the mindset and cultural shift within the existing workforce, all changes need a dedicated change approach accompanied by continuous coaching of the main stakeholders.

It’s not that you can learn “cloud” once and then you are done and ready for the future. Things change very fast in the cloud – and that’s good! However, it’s important to understand that moving to the cloud needs a change in how organizations have done things before. It is a change of mindset in approaching projects in a more agile way, from a people, cost, and technology perspective. Only a joint change of mindset within both business and IT will allow the enterprise to leverage all the opportunities for innovation. And connecting these opportunities with the organization’s business strength will drive that differentiation we mentioned earlier. This openness, collaboration, and learning allow the organization to innovate and even create new markets and is key to being a successful “innovator” in the future.


Yeah, I completely agree. When we look across why organizations are looking to leverage things like cloud, one of the top reasons is because of the innovation piece. How can you implement technology in a way that’s quick and easy, that doesn’t necessarily come with the burden of infrastructure and other legacy processes? You’ve got to figure that piece out. There’s no doubt that IT professionals are one of IT’s most valuable resources, but the jobs that they came into that organization for are quickly disappearing, as that pace of change that Marc talked about is happening at such a great rate.

80% [of employees] said they lack both the skills they need both for their current role and their future career.”


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“Organizations can no longer expect to source and hire enough people with all the capabilities they need; they must move and develop people internally to be able to thrive.”


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To tackle these issues, organizations need to put into place a program of work that allows their teams to up-skill. That requires investment from them and investment from employees. Implementing the technology is really the ‘easier’ part of this, but changing your teams and changing your process is the bit that’s actually going to deliver you success. 

And once the skills are in place, how can an organization ensure business success through having the right technological underpinnings?


If you look at what the latest trends are, blockchain, IoT, ML, AI, autonomous vehicles… All of those things are connected by one thing: data. They’re either creating it, using it to drive value, streaming it, or collecting it. So data is at the heart of everything and whether they realize it or not, all organizations are going to be data-driven if they want to not just survive, but thrive. To get there, you’ve got to have a good understanding of your data and you need to be able to quickly sort, analyze and derive value from that data, wherever it’s coming from and whatever you’re using it for.

“Organizations often must excel at a wide range of practices to ensure AI success, including strategy development, pursuing the right use cases, building a data foundation, and possessing a strong ability to experiment.”


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The faster you understand both the data that you currently have, as well as the new data that’s coming in, the easier you’ll be able to go and deliver on those innovative technology trends and adopt them at the speed that’s required to get any value from them.


Yes, I totally agree. And to add onto that point with an example, what businesses see right now is that through adoption of innovative technology (eg. AI like neural networks and deep learning), they can change the way they do business by analyzing and predicting much quicker. With these insights, they can pivot their business plans accordingly, for example, to dramatically reduce costs or tap into new markets. The main challenge is to get access to adequate data and to train and operate the AI models. Therefore, a flexible data foundation, which can grow exponentially, is one of the key building blocks of competitive advantage now and in the future.

Window for competitive differentiation with AI is quickly closing

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We touched on hybrid cloud and the role that it will play in the adoption of these technology trends, but what does this mean in reality? With private cloud, multi-cloud, and hybrid cloud all viable strategies and approaches, how do you know which is the right one for you?


Whether you choose a private cloud, multi-cloud, or hybrid cloud depends on what you want to achieve. If you follow a cloud-only strategy, you will have some challenges because you need to transform your complete organization from its legacy systems to the cloud. In my experience, these kinds of huge programs usually fail or even increase the costs, at least in the short run.

Therefore you should pick your cloud strategy based on specific use cases and security considerations. Then start the cloud-journey to help your organization to make these use cases a reality. The organization will need to adapt to the cloud technology, processes, skills, and then gradually build cloud-ready applications. 

“…companies need to realize that hardware isn’t a commodity and that cloud architectures—and talent acquisition decisions—must be driven by mission-critical business needs and workloads.”


Modernizing your architecture? Think hybrid and multi-cloud


I agree and think that if you look inside most organizations, they will need to run some of their applications, workloads and data sets on-premises and some on the cloud. What they’ve got to figure out is how to do that in the most efficient way possible. Because if you suddenly start to deploy applications, workloads, and data sets in different clouds, you’re very quickly building up siloes, and barriers that IT have been trying to dismantle appear again. The way to address that deployment in an efficient manner is to drive the cloud strategy from the enterprise data strategy, thereby making the most informed decision possible.

A hybrid cloud environment for data is being referred to in the market as an enterprise data cloud. In this context, the enterprise data cloud is necessitated by modern data architecture, which in turn is informed from the enterprise data strategy. So, everything is linked by the foundation of the data strategy. That’s a game-changer compared to what it’s been previously – having the data there, but not using it (or being unable to use it) to make an informed decision in a timely way. 

So, when we talk about hybrid cloud environments for data, what we mean is: how do you use a technology platform to provide consistency (in experience, security and governance) across different locations (public cloud, on-premises), allowing you flexibility and choice around data and workload placement, without lock-in and creating siloes. If you can figure out how to provide consistency in a secure way across different locations, you’re implementing a flexible and agile hybrid cloud strategy. If you don’t use a common technology platform, you are making things really complex and suddenly that innovation that you’re trying to deliver becomes impossible because you’re just drowning in management overheads. 

Let’s zoom in on how to achieve that agility. How do organizations go about implementing and executing a successful hybrid cloud strategy for data and analytics? 


We defined the successful hybrid cloud strategy for data and analytics as providing consistency (experience, security, governance) across different locations, with flexibility around data and workload placement, without vendor lock-in or creating siloes. For most if not all organizations, an enterprise data cloud will provide them with the easiest way to implement a successful hybrid cloud strategy. An enterprise data cloud is defined as a technology platform that allows you to deploy to any cloud or data center (private, public or both in a hybrid mode), delivers capabilities for the complete data and analytics lifecycle (data flow right through to machine learning), providing consistent data security and governance and that is open (from both an open-source technology and API perspective).


No company can switch completely from on-premises to cloud-only immediately, with all systems – even if that is the desired goal, hybrid cloud will naturally be the interim stage and sometimes also the overall goal. Therefore, it’s important for all organizations today to consider.

With the complexity hybrid cloud brings, comes the need for diverse knowledge across each of the clouds – an increasingly big challenge for CIO organizations. Another challenge is to have an integrated security and metadata concept across all environments. Obviously, you don’t want to develop siloed security models for each cloud provider, so you need to have one security strategy overall, which is then applied for each of the clouds. We have seen clients adopt Cloudera to mitigate that complexity. This moves the knowledge focus from different environments onto one platform, without the need to re-implement current applications. So that’s one way you can adapt for a hybrid cloud strategy. 

“Executives should also consider deploying machine learning and other cognitive tools systematically across every core business process and enterprise operation to support data-driven decision-making.”


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In terms of the big innovative projects you’ve both mentioned, including AI, IoT, blockchain and autonomous vehicles, what’s the key to success there for a business?


While the boardroom is talking about machine learning, AI, and blockchain, the reality is that most organizations still haven’t implemented a data strategy to address the basics – even though they are surrounded by data and understand that there is value locked inside of it that needs to be found.

Without exception, every organization is going to become a data-driven organization, so you’ve got to quickly figure out how to organize, sort, and get value out of data to stay relevant in your market. To start, you need a data strategy that recognizes this shift and that has buy-in from the boardroom. You can then start to explore basic functionality such as data engineering and ingest processes, moving to more advanced things such as ML, as you build capability and experience.


To build on Paul’s point, I think it’s important to not only focus on technology and data because the technology and data itself is not actually bringing any value when not used adequately. The key is to embed technology and data into your enterprise strategy, into your organization, and into your processes – because only if it is embedded you can drive business value and competitive advantage.

An example of this competitive advantage might be that you’re able to develop and deliver new products to your offline stores within a couple of days, instead of months. To identify these topics, ask yourself:

  • What is meaningful for your business?
  • What is it that you can’t do today that you wish you could?
  • Which data and its insight is a crucial ingredient for these?
  • What are the priority topics within these categories? Secondly, how can you derive value and insight within these topics using technology?

Finally, embedding these innovations into your processes across the business will ensure success at every level. The integration of data and technology is the linchpin for these innovations.


And at the same time, all of that is completely irrelevant if you can’t do it in a secure and governed fashion. We live in a world where rules and regulations are placed upon all organizations and having control of your data and visibility into your data, as well as understanding where your data has been and who’s touched it, is as important as what you’re trying to do with that data, the outcome and what you’re trying to derive. 

Thanks for reading this blog. In the next one, we will address how to address your hybrid environment with the additional complexities that security and governance can add. Come back soon to read more. In the meantime, feel free to reach out to our interview subject-matter experts if you have any questions:

Marc Beierschoder LinkedIn

Paul MacKay LinkedIn l Twitter

Caitriona Snell
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