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The Hybrid Landscape: Planning The Path To Cloud Migration Success

Jeff Veis
Actian

Data can be hard — knowing where to get it, where to store it, and most importantly, how to use it, are all questions enterprises need to answer. For most companies, this is an ongoing process in which multiple factors and challenges have arisen.

In the Actian Datacast 2020: Hybrid Data Trends Snapshot, we shed light on the challenges of cloud migration and how organizations are leveraging data. Surveying over 300 Chief Information Officers (CIOs) — the IT Decision Makers (ITDMs), and Chief Data Officers (CDOs) — the Data Decision Makers (DDMs), a few key takeaways emerged:

■ Hybrid landscapes are unavoidable

■ There are unexpected complications with cloud migrations

■ Many lessons have been, and continue to be, learned

■ DDMs have very real concerns around data migration

■ ITDMs, DDMs and their teams are challenged in working together

Embracing the Hybrid Landscape

For many enterprises, hybrid environments are unavoidable. Due to the large amount of data these companies already have in existing systems, as well as the various compliance requirements they are mandated to abide by, a cloud-only strategy is not always a viable option. In fact, 85% of enterprises surveyed stated that they have data both on-premise and in the cloud.

Perhaps surprisingly, less than 10% IT departments surveyed have more than 5% of their data in the cloud. This is primarily due to security concerns, cost predictability, regulatory and compliance issues, legacy applications, and budget allocated to the maintenance of existing data warehouses.

For these businesses, cloud migration is an ongoing conversation and requires executives to weigh multiple factors — from existing investments, to skill sets, to service delivery practices — before making the move.

Unexpected Complications with Cloud Migration

The original hype around the cloud included ease of migration, flexibility of use, and dramatic cost savings. Unfortunately, the reality of the cloud has not always lived up to the expectations, particularly around data security, real-time reporting and predictable cost savings.

Regardless of the key driver for moving to the cloud, 70% of ITDMs experienced challenges during the move, while 59% experienced many more complications than they originally anticipated. In fact, less than 20% of ITDMs stated they had a seamless cloud migration experience. Comparing these statistics, companies have a higher probability of hitting roadblocks than having a perfectly smooth experience, so something to consider and be prepared for.

While in many cases digital transformation has been equated to cloud migration, the requirements and needs of one business often do not match those of a different company. The digital transformation journey of each company is unique, and the chosen cloud strategy should reflect an organization's specific needs.

Lessons Learned from Cloud Migration

In looking back at past migration efforts, more organizations are realizing just how unique and varied transformation is, even across their own business units. In fact, 63% of ITDMs stated they would handle the migration process differently the second time around. For instance, 37% said they underestimated the project complexity, 29% said they did too much at once, and 27% said that they did not sufficiently understand the tools.

To combat these would-be challenges in the future, ITDMs need complete visibility into potential complexities before beginning the journey, and must better understand the importance of adequate preparation, workload selection, education and support.

Ultimately, a cloud migration journey should benefit the company — whether from a cost saving, compliance, security, or other business requirements. If that means taking a bit more time at the beginning to choose the proper cloud strategy that works best, then build that into your roadmap from the start.

The Top Concerns of Data Decision Makers

The desire for real-time data analytics was most often cited as the driver for cloud migration, according to the survey. However, even with so much data at our fingertips, many organizations are still not using that data to its fullest potential.

Nearly 6 in 10 DDMs said they are spending more time, rather than less, on traditional reporting. And while traditional reporting can still drive business impact it was reported that only slightly over half of the data available is actually being used to drive impactful business decisions. This means nearly half of an organization's date is being "left on the table."

IT and Data Teams - Working Together

Due to the proliferation of data that enterprises experience, its effective use comes from IT and data teams working together. Here the survey reveals a "tale of two cities" with IT teams being more likely to say they work well with the data team, while data teams are more likely to say that the two teams have material differences. At the core of this difference of perception is a core misunderstanding of each other's needs and constraints. For instance, DDMs state security and timely data as the top two challenges they experience when working with the IT team — they don't understand why it's so hard to have ready and secure access to the data they need.

As the needs and requirements of each of these teams continues to change, particularly within the IT organization, the skills needed will also change. Over time, this shift is likely to result in closing the gap of understanding between providers and consumers of data.

Data is both our greatest commodity and greatest challenge. Understanding what a specific organization needs in terms of cloud strategy, and the best course of action for implementing that strategy, is the pathway to success. Given the impacts from the pandemic, and other factors, agility is paramount to today's data driven enterprise, but so is cost containment, system complexity and capability. Take the time to plot out the strategy that is most beneficial to the company — a hybrid roadmap is likely what will get you to the next level.

Jeff Veis is CMO at Actian

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The Hybrid Landscape: Planning The Path To Cloud Migration Success

Jeff Veis
Actian

Data can be hard — knowing where to get it, where to store it, and most importantly, how to use it, are all questions enterprises need to answer. For most companies, this is an ongoing process in which multiple factors and challenges have arisen.

In the Actian Datacast 2020: Hybrid Data Trends Snapshot, we shed light on the challenges of cloud migration and how organizations are leveraging data. Surveying over 300 Chief Information Officers (CIOs) — the IT Decision Makers (ITDMs), and Chief Data Officers (CDOs) — the Data Decision Makers (DDMs), a few key takeaways emerged:

■ Hybrid landscapes are unavoidable

■ There are unexpected complications with cloud migrations

■ Many lessons have been, and continue to be, learned

■ DDMs have very real concerns around data migration

■ ITDMs, DDMs and their teams are challenged in working together

Embracing the Hybrid Landscape

For many enterprises, hybrid environments are unavoidable. Due to the large amount of data these companies already have in existing systems, as well as the various compliance requirements they are mandated to abide by, a cloud-only strategy is not always a viable option. In fact, 85% of enterprises surveyed stated that they have data both on-premise and in the cloud.

Perhaps surprisingly, less than 10% IT departments surveyed have more than 5% of their data in the cloud. This is primarily due to security concerns, cost predictability, regulatory and compliance issues, legacy applications, and budget allocated to the maintenance of existing data warehouses.

For these businesses, cloud migration is an ongoing conversation and requires executives to weigh multiple factors — from existing investments, to skill sets, to service delivery practices — before making the move.

Unexpected Complications with Cloud Migration

The original hype around the cloud included ease of migration, flexibility of use, and dramatic cost savings. Unfortunately, the reality of the cloud has not always lived up to the expectations, particularly around data security, real-time reporting and predictable cost savings.

Regardless of the key driver for moving to the cloud, 70% of ITDMs experienced challenges during the move, while 59% experienced many more complications than they originally anticipated. In fact, less than 20% of ITDMs stated they had a seamless cloud migration experience. Comparing these statistics, companies have a higher probability of hitting roadblocks than having a perfectly smooth experience, so something to consider and be prepared for.

While in many cases digital transformation has been equated to cloud migration, the requirements and needs of one business often do not match those of a different company. The digital transformation journey of each company is unique, and the chosen cloud strategy should reflect an organization's specific needs.

Lessons Learned from Cloud Migration

In looking back at past migration efforts, more organizations are realizing just how unique and varied transformation is, even across their own business units. In fact, 63% of ITDMs stated they would handle the migration process differently the second time around. For instance, 37% said they underestimated the project complexity, 29% said they did too much at once, and 27% said that they did not sufficiently understand the tools.

To combat these would-be challenges in the future, ITDMs need complete visibility into potential complexities before beginning the journey, and must better understand the importance of adequate preparation, workload selection, education and support.

Ultimately, a cloud migration journey should benefit the company — whether from a cost saving, compliance, security, or other business requirements. If that means taking a bit more time at the beginning to choose the proper cloud strategy that works best, then build that into your roadmap from the start.

The Top Concerns of Data Decision Makers

The desire for real-time data analytics was most often cited as the driver for cloud migration, according to the survey. However, even with so much data at our fingertips, many organizations are still not using that data to its fullest potential.

Nearly 6 in 10 DDMs said they are spending more time, rather than less, on traditional reporting. And while traditional reporting can still drive business impact it was reported that only slightly over half of the data available is actually being used to drive impactful business decisions. This means nearly half of an organization's date is being "left on the table."

IT and Data Teams - Working Together

Due to the proliferation of data that enterprises experience, its effective use comes from IT and data teams working together. Here the survey reveals a "tale of two cities" with IT teams being more likely to say they work well with the data team, while data teams are more likely to say that the two teams have material differences. At the core of this difference of perception is a core misunderstanding of each other's needs and constraints. For instance, DDMs state security and timely data as the top two challenges they experience when working with the IT team — they don't understand why it's so hard to have ready and secure access to the data they need.

As the needs and requirements of each of these teams continues to change, particularly within the IT organization, the skills needed will also change. Over time, this shift is likely to result in closing the gap of understanding between providers and consumers of data.

Data is both our greatest commodity and greatest challenge. Understanding what a specific organization needs in terms of cloud strategy, and the best course of action for implementing that strategy, is the pathway to success. Given the impacts from the pandemic, and other factors, agility is paramount to today's data driven enterprise, but so is cost containment, system complexity and capability. Take the time to plot out the strategy that is most beneficial to the company — a hybrid roadmap is likely what will get you to the next level.

Jeff Veis is CMO at Actian

Hot Topics

The Latest

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...