Total cost of ownership as a calculator for the use of cloud solutions
Modern data architectures and data analytics offer companies a wealth of benefits. The use of real-time data, machine learning and cloud computing makes it possible to make better decisions and optimize operational processes. However, financial aspects naturally play a major role in the decision for or against cloud solutions. It is therefore helpful to calculate the total cost of ownership (TCO) when implementing new technologies.
TCO refers to all costs associated with owning and operating a system and can play a major role in assessing whether a system is profitable or not. In this blog article, we explain how TCO is calculated and look at the importance of TCO in modern data architectures and data analytics. We show how these systems can lead to time savings, overhead reduction and maintenance effort reduction - and thus to a reduction in TCO.
Calculation of the TCO
Calculating the total cost of ownership (TCO) in relation to no-code/low-code-based data architectures and data analytics can be complex. The following costs should be considered:
1. platform costs
The cost of using the no-code/low-code platform, including license and subscription fees, upgrades and support.
2. IT infrastructure costs
The costs of the IT infrastructure, such as servers, storage space, network and security equipment required to support the data architecture.
3. development costs
The cost of creating and maintaining data processes and dashboards, including labor costs for developers, testers and analysts.
4. training costs
The cost of training and education to prepare employees to use the platform and facilitate the implementation of data processes and dashboards.
5. support costs
The costs for IT support and help with technical problems or troubleshooting.
How companies can reduce their TCO
Companies can take various measures to reduce TCO. Here are the most common ones:
Setting up modern data architectures and data analytics
Modern data architectures and data analytics can reduce maintenance costs and the time required, resulting in a faster ROI. By automating processes and using observability tools, systems can proactively point out problems and identify sources of error before a failure occurs. This reduces maintenance effort and leads to less downtime. Orchestration tools can also be used to customize and automate the frequency of data updates. This enables companies to make faster and better decisions, reduce manual tasks and optimize workflows.
Use of a "fully-managed" platform with no-code/low-code capacities
Using a single platform for all steps of the data process ensures a simpler and more cost-efficient pricing structure, avoids oversizing of the IT infrastructure and the implementation of processes and dashboards with higher automation and lower maintenance costs. A popular example of this is the Y42 DevOps Cloud, as it meets all the criteria of a modern data stack. No-code/low-code-based approaches in particular offer advantages such as faster development and implementation of data processes and dashboards, less dependence on IT experts and greater flexibility when making changes and adjustments. These factors can reduce the overall TCO and lead to a faster ROI.
Use cloud infrastructure
Many companies can massively reduce their overall costs if they decide to switch to cloud-based technologies. They no longer have to operate and maintain their own servers and storage capacities, but can use these services from third-party providers. Several factors contribute to this.
Companies no longer need to invest in expensive hardware, server space, network devices and staff to manage these resources after moving to the cloud. According to a study by IDC, companies that migrate to the cloud can reduce their IT expenditure by an average of 14.2%.
Scalability is another important advantage of the cloud. With cloud computing, companies can respond quickly and easily to the needs of their business by adding or removing resources. Required capacities can be adjusted in real time, resulting in better capacity utilization and resource utilization.
In addition, many cloud providers offer pay-as-you-go models where customers only pay for the resources they actually use. This means that companies do not have high upfront costs and only pay for what they actually use. A study conducted by RightScale in 2019 found that companies that use an optimized cloud infrastructure and a pay-as-you-go model can save up to 64% in costs.
Another advantage of cloud computing is the ability to reduce downtime. Cloud computing enables companies to operate their IT infrastructure in redundant data centers. In the event of a failure, another data center can step in. This reduces downtime and ensures constant availability. In addition, overhead costs such as electricity, cooling and personnel for maintaining the infrastructure become obsolete.
Cloud-based and cost-saving: out-of-the-box data management tools
Data management is already a high priority in many companies. In many places, however, implementation remains below their capabilities in terms of both organization and technology. One of the biggest challenges is selecting suitable tools if you want to build a modern data stack. A Modern Data Stack is a layered system of automated services that collect, combine, analyze and leverage the value of data. At the most basic level, a modern data stack bridges the gap between raw data on the one hand and data analytics on the other. However, this tool landscape, which can be used to process data, does not have to be put together in-house, nor does it have to incur high costs.
An excellent example of a tool that combines all functions in one is the Y42 DataOps Cloud from the provider of the same name. Y42 has natively integrated the best tools for each step of the data pipeline so that users can manage their pipelines via no-code and code interfaces and control them through data governance. The platform thus manages a modern data stack and is based on the Snowflake and Google BigQuery cloud data warehouses. Users build their data pipelines on this platform and make the most important data accessible for their company.
Companies that want to rely on established and future-oriented tools can rely on a fully functional modern data stack in the cloud with a solution like Y42. No one has to deal with the selection of tools within a data stack at a detailed level. If such a managed stack is chosen, the costs for development, training and support are much lower.
Reduce TCO with new technologies
The total cost of ownership can be massively reduced with new technologies, and initial investments in new technologies, structures and processes pay for themselves within a very short time. In addition to a cross-company cloud strategy, this requires a well-calculated selection of data management tools that precisely meet the company's requirements. In line with the motto "Start small, scale big", companies can impressively expand their cloud initiatives if they try out future data projects on a small scale and scale them up as required with the help of flexible cloud technologies.
And what does it cost to get started with cloud solutions? Of course, we can't put a price tag on the cloud. Because as unique as every company is with all its requirements, cloud-based solutions can be put together individually. Each company should carry out its own total cost analysis, taking into account its own parameters. However, we can already predict the result: The switch will save costs. We are happy to help.
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