Evaluating a Data Integration Platform: The ROI Way
When you focus on the upfront price you lose sight of the hidden cost and risk associated. It’s very important to understand the tradeoffs and make an informed decision.
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How many of you look into the nutritional information and ingredients before you buy a packaged food product? As consumers, we perceive value based on how much we can decode the ingredient labels and match it to the price at which it is offered. While it’s easy to relate an ingredient like refined sugar to unhealthiness, it’s another thing to rightly estimate the hidden price that you pay for consuming that sugary food.
In IT things are not getting any different. When you focus on the upfront price you lose sight of the hidden cost and risk associated. It’s very important to understand the tradeoffs and make an informed decision.
Let me take three examples from the data integration and management market and explain.
There are several components of a broader data management landscape starting from data integration, data ingestion, data transformation, data governance, data quality, data preparation, data discovery, and data delivery. Instead of a simple TCO, a business value assessment that factors in the financial benefits for each component provides a holistic picture of the gains and losses that you might incur. To start with, let’s see how we can evaluate these three capabilities and understand the way to calculate ROI.
Multiplying Effect of Advanced Features
Emerging technologies have the power to change the way you compete in your industry. Often times companies focus on incremental changes instead of adopting disruptive technology that offers a multitude of improvements in terms of performance. For example, there is always pressure on integrators to reduce data processing time and help speed up the decision-making process for the business. As an architect, you should choose a data platform that helps you combine best-of-the-breed technologies for the multiplying effect it has on speed, productivity and performance. With a serverless, Spark engine and NVIDIA GPU-enabled, cloud-native data integration platform you have the opportunity to increase data processing speed by almost 5X and to drive 72% lower TCO. A future-ready data platform would allow you to explore and adapt multiple advanced technologies. Compare and quantify the benefits, the risk, and the cost associated with each platform.
Depending on available skill sets, growth patterns, compliance guidelines, and cost governance structure you will have the flexibility to decide how much you want to manage the instances on the cloud. Think long term and consider a cloud data management platform that allows you to switch deployment patterns with minimal disruption. You can opt for serverless data integration and switch back to cluster management if need be without changing products or compromising on features. One way to evaluate is to run a complex data transformation in the cloud and then switch to serverless and see the cost difference, the time needed, and missing features. A cloud-agnostic platform will drastically reduce the cost of switching or migrating workloads to a different cloud provider.
Power of Collaboration
Productivity increases when you remove the friction of handoffs between data governance, data catalog, or data integration solutions. From sharing skill sets to reducing downtime, a comprehensive cloud-native data management platform is much more beneficial financially as opposed to cloud-specific products, disparate tools, and hand-coding. With a simple and familiar GUI and seamless integration among different components of a data management platform, the team can take a holistic view and resolve issues faster. Your company can take a more inclusive approach as it gets easier to discover, govern and process data by both technical and non-technical users. If the number of new users goes up and the number of data integration requests to IT goes down then it indicates that the team is getting more productive.
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