The Real Value of Data Streaming: Benefits, Costs, and Key Insights
The current landscape of big data dictates new rules and sets higher standards for businesses. No doubt, the amounts of data generated and consumed are increasingly growing. And the latest estimates show impressive data growth.
In 2023 alone, 120 zettabytes of data were created, and this is not a limit. This number is forecasted to reach more than 180 zettabytes by 2025. But what does this mean for companies?
When businesses analyze their data effectively, they become more advanced in decision-making. The right approaches to managing and operating data drive the development of smarter business strategies. As a result, enterprises obtain a better vision of market demands, identify potential risks, make predictions, understand customer preferences, and create personalized offers.
Data streaming has become a cornerstone of modern business operations, and understanding the technical and cost implications is critical before diving in. To make the most use of data, businesses need effective processing tools. As a CTO, you need to weigh the options carefully. Before providing cost estimates and a project plan, development teams typically collaborate with clients to discuss the technical aspects of the future data streaming solution.
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Data Streaming's Business Benefits
Data streaming is all about handling a continuous flow of data the moment it comes in—no delays, no waiting for batch processing. It makes sense for organizations that rely on real-time insights to drive critical decisions and keep their operations agile.
Beyond better decision-making and the ability to offer more personalized customer experiences, data streaming offers some serious advantages.
For one, it saves both time and money. By automating data processing as it happens, you reduce the manual labor typically needed for data wrangling, freeing up your team to focus on more impactful tasks. It also provides a holistic view of your operations, allowing you to proactively address technical issues before they escalate into costly downtime.
Take engineering or manufacturing as an example. Data streaming can continuously monitor equipment performance, flagging potential malfunctions before they lead to outages. The same real-time nature applies to cybersecurity—it’s about catching threats, anomalies, or compliance breaches as they happen, not after the fact. By reacting instantly, you reduce the risk of data loss, fraud, or anything else that could compromise your infrastructure and business continuity.
What Will it Cost Me?
Given these clear benefits, more businesses are investing in data streaming solutions to boost their performance and earn more profit.
The 2024 Confluent Data Streaming Report has shown that 84% out of 4,110 IT leaders have already enjoyed a 2x to 10x return on data streaming investments, while 41% of respondents reported an ROI of 5x or more.
When it comes to the amount of such investments, there is no fixed price for any project or business. Typically, the following factors impact the final cost of the solution:
- Project scope
- Technologies
- The volumes of data to be processed
- The complexity of integration with the existing company’s IT infrastructure
- Any resources required for development, support, and maintenance.
Development of a data streaming solution can cost from $150,000 to $1,000,000+ based on the factors listed above.
Technical Trade-offs for Data Streaming Solutions
Before providing the cost estimates and project plan, software development companies like ScienceSoft discuss technical aspects of the future data streaming solution with their customers. This is an essential step, as the choice of tools will impact the project price.
Open source tools like Apache Kafka, Apache Flink, or Apache Spark Streaming are powerful, flexible, and save on licensing fees. However, they come with their own set of challenges. These platforms require significant management, customization, and scaling investment, so the operational overhead may offset the up-front cost savings. You need skilled engineers who understand the ins and outs of these systems to make sure everything runs smoothly.
On the other hand, cloud solutions like Amazon Kinesis, Google Cloud Dataflow, or Azure Stream Analytics offer the convenience of managed services—but at a price. Depending on your data volume, events per second, and computing needs, costs can range from a few hundred to several thousand dollars per month. It’s the classic trade-off: operational convenience versus cost control.
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Infrastructure decisions also play a pivotal role in your planning. Opting for on-premises servers means accounting for hardware and maintenance costs, whereas cloud-based infrastructure provides flexibility, with spending directly tied to usage. This choice often boils down to your organization's appetite for managing physical infrastructure versus leaning into the scalability and operational simplicity of the cloud.
Integration costs are another consideration. Streaming solutions need to play nicely with your existing IT systems—and customization is usually required. This means extra budget allocation, but it's a non-negotiable if you want your data streaming solution to deliver real value. Especially if you're dealing with databases and other data storage systems, seamless integration is key to keeping your operations streamlined.
Ongoing support and maintenance is also something you need to factor into your total cost of ownership. Infrastructure—whether on-prem or cloud—requires constant monitoring, periodic updates, and sometimes significant scaling efforts. In many cases, additional monitoring and analysis tools are necessary, which means further investments to maintain a stable, secure data pipeline.
Use Cases
Data streaming solutions are no longer niche—they've become foundational across a wide range of industries, from finance to healthcare, telecom to logistics. When implemented effectively, they push businesses to the next level, turning data into actionable, real-time insights.
- Healthcare: Data streaming helps monitor patient health in real time. Devices like fitness trackers, medical sensors, and smart monitors collect data such as heart rate and blood pressure, enabling medical professionals to react immediately to critical changes. This kind of rapid response is especially crucial in emergency scenarios, where every second counts.
- Social Media: The sheer volume of real-time data—likes, shares, comments, clicks—is staggering. Leveraging this data effectively means companies can monitor user behavior and engage with brand mentions as they happen. This instant feedback loop helps refine marketing campaigns and enhances user engagement, driving both retention and growth.
- Supply chain and logistics: Data streaming brings operational efficiency to a new level. It can monitor the technical condition of vehicles, predict and prevent breakdowns, and track cargo in real time, ensuring deliveries stay on schedule. If there’s an accident or traffic jam, streaming data allows for rerouting on the fly, minimizing delays.
- Inventory management: Allows for precise analysis of sales, supply levels, and product demand, helping to avoid overstock or stockout situations.
Takeaways
When businesses work with their data effectively, they enhance their service quality, optimize processes, and reduce risks. Obviously, data streaming is a new-era innovation that grants a competitive advantage to companies and opens up a world of new opportunities for growth and development.
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