Cloud Data Warehouses - May 27 2021

Why Does Total Cost of Utilization Make More Sense for Cloud Data?

For cloud data infrastructures, Total Cost of Utilization (TCU) analysis definitely makes more sense than Total Cost of Ownership (TCO analysis), especially keeping in mind the sweeping changes brought to the table by cloud data warehouses and platforms.

For businesses looking to work with data using a cloud data framework, it’s vital to have a sense of ROI by carrying out the right cost-benefit analysis. To this end, it’s fundamental to know exactly how to calculate the costs associated with cloud data. For many organizations, Total Cost of Ownership or TCO has been the major KPI when it comes to working with data. However, if you consider the current landscape, where most businesses open the door for a cloud-based solution over an on-premise solution, it becomes obvious that a different approach would be more effective.

Let’s take a look at how TCU makes more sense for cloud data, and how to make TCU analysis work for you.

What is Total Cost of Utilization?

In order to understand the concept of TCU, it is important to clarify how it’s different from the TCO approach. For on-premise data warehouses, the TCO analysis works because the organization actually needs to own the hardware and software that makes up that infrastructure. Then, the costs associated with overhead, maintenance, and staffing can be calculated to form a rough estimate of the TCO.

When it comes to cloud data platforms, organizations don’t theoretically “own” anything. The entire infrastructure is in the cloud and the service provider is the entity that is managing the ownership costs. Therefore, in such circumstances, we come to TCU analysis to understand the ROI of cloud data services. 

Since more and more businesses are making the switch to the cloud, and the concept of ownership does not jive with cloud services, the importance of TCU analysis has increased over the years.

TCU takes into account not only the costs of utilizing cloud resources for data operation, but also the cost optimizations that come into the picture specifically due to a move to the cloud. With TCU, the focus shifts from 1) What you own to what you use, 2) How your costs have different components than on-premise solutions, and 3) How you can achieve better cost-efficiency using the elastic model that the cloud provides.

In short, TCU is the sum of your total costs, tangible, and intangible, when you are using a cloud data infrastructure. Here are a few important points to remember when trying to calculate 


  • With a cloud data infrastructure, you have the advantage of an elastic system that can scale and grow as per your needs. This means that you do not need to design a system for peak loads. Consequently, you do not need to budget for peak loads.
  • Storage costs can be lower for cloud data solutions as you can employ different forms of compression to reduce your storage footprint.
  • Workloads in the cloud are typically carried out faster, which leads to cost-benefits arising from speed of operation and results.
  • Costs can get significantly lower with a cloud data solution as much of the maintenance, operations, and administration is handed over to the service provider. In addition to saving on hardware and software, you can also save costs on laborthese fronts as you do not need to employ expert staff for these tasks.

Therefore, the TCU approach marks a major shift from the capital outlay cost model, moving instead to an operational expense or OpEx model. This is due to the changing landscape of data storage and analysis infrastructure models, owing to the advent of Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).

What is cloud computing utilization?

When it comes to calculating TCU, several generic factors as well as several factors unique to the cloud architecture need to be taken into account. Here are some important points for consideration to ponder:

  • With a cloud solution, a lot of the operational aspects of maintaining a data warehouse can be offloaded to the cloud vendor. This includes purchase, deployment, maintenance, and upgradation of the expensive hardware required for on-premise solutions. Also included in this are the software costs, networking costs, and operational overheads. You can also do without the costs associated with a highly skilled staff to manage the complexities of the infrastructure.
  • With a cloud solution, the overall complexity of the entire process can be markedly reduced, leading to a quicker time to results. With much of the process offloaded to the cloud vendor, your efforts can concentrate on business-critical workloads.
  • You can save costs by replacing the high costs of a perpetual software license with a subscription licensing model.
  • With data compression, storage footprints can be reduced and there is a corresponding reduction in storage costs.
  • With complete control over computing capacity, you can have faster resolution of computing workloads.
  • Finally, the most important point here is computing elasticity. You can pay for as much computing engine power as you need, expand, or contract that requirement any time you want at minimal cost, and save money in terms of elastic capacity as well as licensing.

Cloud utilization is a function of all of these factors. The focus moves from ownership to efficiency and what you are using the solution for.

How are costs generally charged for cloud resources?

Usually, costs for cloud resources are divided between a few areas. Here are some of the important parameters you can use to calculate costs:

  • Storage – Storage is usually charged per unit, with most providers presenting a flat rate per GB calculated monthly or yearly. Some providers can provide volume discounts or reduced pricing for storage that does not need to be accessed frequently.
  • Compute Engine – In most cases, you would use cloud data warehouses for queries and analysis, which uses compute power. You can purchase compute engine slots of various power and characteristics while providers would usually charge in terms of number of queries over time.
  • Integrations and Data Intake – In some cases, cloud providers might charge you for specific integrations with third-party solutions and for data intake connectors.
  • Bandwidth – Finally, for data transfers in and out, providers usually charge customers based on the data volume. In most cases, these costs are associated with an outward flow of data.

How much does it cost to implement cloud?

A move to the cloud can be accomplished in many different ways. Usually, the less you adapt and rearchitect your existing applications to the cloud platform, the less time it takes to make the switch and the less it costs. While a complete refactoring might be more expensive and take more time, the one-time costs and time are offset by the fact that you can make the best and most efficient use of the special features and functionality that cloud platforms usually afford.

The lowest cost, for most organizations, would be a lift-and-shift approach where existing applications are just taken as-is and put on the cloud. While this approach might require you to deal with failures and bugs, the process can be completed fast and for very little cost. If your workloads are time-critical and you want to implement cloud technology with minimal downtime and cost, this might be the way to go.

For any other use case, you can make use of partial or total refactoring to take better advantage of the cloud technology. In such cases, the up-front costs might be higher but the benefits over time will be much greater by adopting the full benefits of cloud technology tend to balance things out. A middle-of-the-road approach with partial rearchitecting can present a balance between time and cost-effectiveness, and the degree to which you utilize the unique features of the cloud.

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