Success in the Cloud | Part 1 of 5
Cloud-based data analytics allows organizations to derive value from their data in ways that traditional on-premises solutions cannot. Organizations globally have already figured this out, and are now on journeys to realize the potential of analytics in the cloud. Most are about halfway through their cloud journey. What remains for most is getting past the “lift and shift” mentality that characterizes some cloud migrations, and educating higher-ups on the benefits cloud infrastructure can yield — ultimately driving buy-in.
While cloud migrations are well underway, few companies have completed the journey.
There are very few mid-market organizations utilizing cloud analytics to their potential. In a survey of 100 mid-market organizations, 66% are about halfway through their cloud transformation journeys; the number reporting fully modernized cloud-based data ecosystems was only 6%.
Lack of stakeholder alignment is a primary obstacle to successful transformation.
How can the 66% close the gap? Ultimately it is about understanding and being able to communicate the benefits of such a cloud transformation. What inhibits cloud adoption is not lack of value, it is misunderstanding.
The pandemic provided a live test case for the usefulness of cloud-enabled technology. Suddenly teams were separated by geography, unable to communicate in person. For the marketplace, this meant being able to access data remotely was no longer a nice-to-have, it was a legitimate competitive advantage that allowed prepared businesses to continue operating.
Beyond closing distance, organizations are discovering cloud enablement to be a useful lever of data governance. By its nature, data stored in the cloud is highly available and therefore easily accessible. Therefore, if a company has workers in Maryland, Alaska, and Hawaii, with the right preparation, access to sensitive data can still be distributed, controlled, and monitored as easily as on-premises infrastructure. Moreover, having one central source of truth can remedy the problem of siloed-off logic, “rogue spreadsheets,” and nebulous business logic.
Today these tools remain incredibly valuable. While the pandemic has abated some, the reality of remote teams remains, leaving cloud-enabled tools to bridge physical divides.
Common roadblocks mid-market companies encounter.
Many organizations experience the same roadblocks on the road to fully realizing the value of the cloud. Among them are missed opportunities to revise data practices during implementation, reliance on outdated data management habits, and a non-uniform distribution of value-add within the organization itself.
Evaluation of business process
Moving on-premises data to the cloud lends itself neatly to an evaluation of business processes. What is working well? What is causing problems? And what could cause problems down the road? To squarely miss gleaning the valuable insights from the answers, one might take a lift-and-shift approach to their cloud migration.
Lift and Shift
This approach misses a lot of opportunities. A lift-and-shift cloud migration (also called rehosting) is a 1:1 replication of on-premises data storage models, schemas, and methodologies on a cloud platform. When finishing a lift-and-shift, an organization will have the exact same business logic, databases, and workflows they had before, now on the cloud. This is complete with all the same advantages, bugs, and flaws as the prior system.
Data Management Practices
Outdated data management practices, migrating old and unused data, and a lack of education can hamstring a cloud migration. The lift-and-shift approach without evaluation of internal processes can lead to unneeded costs for the organization, and sap the sustainability from the new system. For example, is it worth moving a 6 GB Excel sheet last accessed in 2003 to the cloud? Or can that file be removed? These are the questions organizational introspection before migration can help to answer.
Non-Uniform Value Add Distribution
A key aspect of planning a successful cloud migration involves managing expectations. Making an organizational shift to cloud data storage won’t necessarily lead to uniform distribution of value-add across an entire organization. A data science team will find more value in a cloud-hosted data warehouse than an inside sales team. However, linking teams of various business functions to the same data warehouse facilitates synergy between them, creating value for all.
The features of a cloud migration are important, but the biggest major obstacle to cloud adoption continues to be executive buy-in. Analytics leaders across industries consistently cite a lack of buy-in from leadership, specifically securing the budget for such a cloud transformation, as their biggest roadblock.
Communication about expectations, costs, and most importantly aligning cloud migrations with organizational goals (in both the short term and long term) is the most important tool for any analytics leader seeking to make the jump to the cloud.
The importance of cleaning house before you make the move.
Moving from on-premises to cloud-based data storage is not at all like flipping a switch. Instead, a cloud migration should be treated as an investment in existing business logic. There are limitations to hosting data on-premises that can’t be overcome due to the nature of the technology, and the way to maximize the existing business logic is by moving it to a new, more available platform.
A cloud migration is something that should only be done once. While a lift-and-shift will technically work, the organization misses the opportunity to improve processes, communication, and do some much-needed “housekeeping” of their data. This is hard work in the immediate term (during the transformation) but will quickly pay off in the short term, with long-term rewards that will compound over time.