I look at Cloud Modernization journeys like modernizing your home. After a home has reached a certain age – you realize it is not exactly the picture of modern. Appliances are getting old, the carpet is worn, the furnace isn’t as efficient as current high-efficiency models, and it just doesn’t feel modern anymore. A homeowner might consider a modernization journey to bring their house up to current standards. This can be as simple as replacing their appliances with new versions – but it can be extended to be as extensive as turning an unused study into a 4th bedroom or replacing all of the insulation in the home to a more energy-efficient option. Depending on the homeowner’s desired level of modernization and budget, these projects can be small or more complex. If you are going all the way to the walls to replace the insulation with modern foam insulation – when you finish the space again – often a homeowner will ‘refactor’ their space with new color walls, carpet and maybe even new trim since this needs to be repaired given the level of construction required.
In this blog post, I’d like to tackle one of the key considerations in a Cloud Analytics Modernization journey – whether it is best to modernize the on-premise technology stack to cloud-based solutions – or if this is the time to also refactor along the way to not only modernize the technology but modernize the process and capabilities as well.
Modernization with Lift and Shift vs. Refactoring
In a Cloud Analytics Modernization journey, many areas can be looked at in terms of modernization at first glance: replacing legacy databases, updating data integration tools and processes and new cloud-based visualization tools. Swapping out on-premises technology for cloud-based versions provides a technology-based modernization – much like a homeowner swapping out appliances and a furnace or water heater for a high-efficiency version.
While this technology upgrade is certainly the key tenant of modernization – moving to new cloud storage and cloud-aware tools – It’s an opportunity to take advantage of this modernized platform and leverage immediate and future business value and years of future return on investment. For example, in these modernization projects, a client might focus only on moving exact copies of tables from Oracle to Snowflake, pushing across the same data integration processes and schedules to the cloud and recreating the old on-premise generated reports in a cloud reporting tool. This is the very definition of a ‘lift and shift’ – mimicking the same capabilities and outcomes just shifted to cloud infrastructure.
While the results of this approach are the easiest to validate and usually the lowest short-term path and cost to cloud modernization– this tends to provide little value to the business community. If all goes well, you provide users with the same reports from the same data from a different place. This is hardly much to get excited about from the business community and certainly makes funding requests more difficult to rationalize. Furthermore, the IT team still must manage the new cloud environment using the same back end of potentially sub-optimal table structures loaded by a hodgepodge of data integration processes built over many years, optimized for on-premise storage technology, then generating reports with metrics and measures defined years ago. The primary goal and measure of success of ‘lift and shift’ modernization project once in production is ‘Does the output look exactly the same?’.
Since you are moving this work to the cloud using new tools, it will all need to be tested and validated again to ensure nothing was missed during the conversion. Automated tools from database vendors, conversion tools and other automation methods can make the move process less manual, but the testing effort remains. The testing and validation effort usually becomes the most expensive part of any migration. Why not take advantage of the investment in testing and validation and consider refactoring into a better model on your journey to the cloud? Just like a house modernization project where the costly demolition down to the bare walls makes it a no-brainer to consider building back with new colors, materials and features. Why wouldn’t you also consider modernizing your data framework and management processes? These functional changes we call ‘refactoring.’
Consider the following areas where refactoring your environment can make life better for both your business user and your IT team:
|Could additional fields or tables be added/expanded to make your analytics more comprehensive?||Does the move to the cloud provide the bandwidth to refresh your analytics more often or the ability to manage volumes of data you didn’t think possible?||Do you have a multilayer load strategy for staging, cleansing, and harmonized data storage? Might this be the time to rework your data architecture?|
|Were some of your integrations built less than optimally? Too many SQL overrides, stored procedures, or other hard-to-maintain code across multiple tools? Is now the time to rebuild the right way to make changes to processes?||Are there data sources that were difficult to integrate before where cloud integration tools can allow easier access? Can you access them better using potentially new Cloud API’s and improved real-time availability?||Can you leverage cloud integration performance advantages to load and process data more quickly? Can you use the power of cloud hardware to refresh faster and calculate more advanced metrics?|
|Do users have ways to get to ad hoc data sets and analytics capabilities to better react to ad hoc needs and desires? Is this the time to deploy a data marketplace?||Do your users understand all the data fields and metrics provided and how they were calculated? Could this be the time to launch a data catalog to describe better what they are seeing?||Is your data secured? Are users given full access to everything exposing data risks, or can you be more granular about who is accessing what and when?|
If you answered yes to any of these questions – now is the time to consider addressing some of these opportunities. In the past, you may not have had the time or budget to fix them because it was working ‘good enough,’ and the cost to go back and rearchitect or consolidate was never possible because of the retesting expense and, most importantly, you couldn’t identify tangible new value because it was not achievable.
The new cloud tools you migrate to will unlock features and capabilities you never had before – mass ingesting datasets, calculating complex analytics, real-time feeds, and a host of other improvements are possible and can be done more cost-effectively while you modernize. So, instead of simply porting your environment to the cloud, your modernization journey may include adding new tables to store a new data source that the cloud integration tools have unlocked. New metrics might be calculated and stored in your new warehouse, providing new metrics and capabilities for your business users. Behind the scenes, you’ve consolidated your data integration tools into a single cloud platform, reducing support costs, and you have re-architected some of your load processes to better take advantage of the cloud tools and bandwidth to provide near real-time data to your users. While this may add cost and time to your conversion – it can be reclaimed using a single testing and validation process. This strategy generates an initiative and a project both business and IT can get behind!
Back to the house modernization analogy – the new high-efficiency furnace and water heater combined with upgraded insulation give you a great piece of mind but not value you can readily appreciate daily. However, they protect and provide visible value to your investment in new hardwood floors, modern wall colors, trim and those needed outlets you could easily add when the walls were opened. These are tangible benefits you can see and feel every day. With a little extra effort and a sound plan, your cloud modernization journey can be equally exciting for your IT and business teams.
Contact us for more information on how CTI can help with your cloud analytics modernization project.
Steve Dulzer is the Cloud Modernization Solution Director at CTI Data.
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