Data Streaming Explained: Benefits, Examples, Vs Real-Time

People have long understood that data is key for driving performance and growth. What more and more are realizing lately is that the data must be fresh to have any impact at all. That’s why traditional batch processing of data is being replaced with data streaming. 

Data streaming allows you to access information in real time as it’s generated from all your data systems. An estimated 90 percent of the largest global businesses will use data streaming to improve their services and customer experience in 2025. 

Streaming data provides you with real-time business and customer intelligence so you can enhance your daily operations, stay on top of emerging trends, or find new opportunities. Learn how it works, its benefits, and what aspects to consider when using a data streaming platform.

What is data streaming?

Simply put, data streaming is the continuous flow and transfer of data from all your sources into your data platform as it’s created. It includes data generated at high speeds or volumes, simultaneously collecting data from all your applications, websites, social media channels, financial and customer transactions, networks and servers, Internet of Things (IoT) devices, business platforms, and more.

Data is collected, stored, processed, and analyzed in real time, so you’re constantly viewing the most up-to-date information. Data streaming is possible due to technology like cloud computing, internet-connected devices, and advanced analytics platforms. 

Streaming data is replacing batch processing of business data, eliminating the need to download your data and reducing the time between data collection and analysis. It can handle numerous data types, changing volumes of data, and high-velocity data without affecting latency. 

Benefits of using data streaming

The greatest benefit of streaming data is being able to understand business operations and customer activities at a deeper level and in real time. Unlike traditional data processing, where information has to be extracted, transformed, and loaded from data pipelines before it can be analyzed and acted upon, data streaming processes new data points as they are generated. 

Data streaming platforms give you quicker access to information so your company can become more agile and respond to changes faster. You’ll also see:

• Reduced costs: Data streaming infrastructure is often less expensive than legacy and batch processing systems since you don’t need to utilize on-premise storage or data warehouses to store large volumes of data for processing purposes. 

• Improved visibility and operational efficiency: You can monitor operations across your business in real time, allowing you to find ways to improve marketing, sales, and financial performance for improved business outcomes. 

• Increased customer satisfaction: Streaming data enables you to respond to changing customer interests or market fluctuations immediately and provide a more personalized experience, improving overall customer satisfaction. 

How data streaming works

Data is created by just about every action through numerous systems and sources. Data is continuously generated and streamed from digital marketing campaigns, IoT sensors, business servers, and by people using apps and visiting websites, just to name a few. For your business to make use of this data, you need the right streaming infrastructure that can ingest and process high-volume and high-velocity data at a continuous pace. 

Data streaming tools consist of two main components: storage and processing. The storage layer needs to quickly and consistently read and record large data streams in sequential order. Then, the processing layer has to connect with the storage to consume the streaming data to analyze and perform computations. Once it completes this process, it can direct the storage layer to remove unneeded data. 

Legacy systems and databases often can’t keep up with modern, complex, fast-moving data streams. Instead, companies are turning to other platforms to help them build stream processing applications that can handle real-time data processing and delivery. These tools can consolidate all your streaming data sources and help you build a fast and scalable processing layer. From there, you can query your data or send it to another output like an analytics or BI tool to create easy-to-understand data visualizations and get real-time reports. 

Batch vs real-time processing

What is data streaming in comparison to batch processing of data? Below, you’ll see how the two processes differ and learn which works best for your business applications. 

Challenges and considerations with data streaming

It can be more challenging to develop real-time data streaming applications due to its complex nature, large volume, and high velocity. Knowing the biggest potential issues and the proactive steps you can take is key to designing a powerful and adaptive data streaming process. Here are some top factors to consider:

Scalability 

Data streaming is a continual process with data volumes that rapidly surge and decrease at any given time. This feature means your ingestion, processing, computational, and storage infrastructure must be operating constantly and offer the scalability your data requires. Consider using cloud-based tools and data storage, which offer the required flexibility and scalability needed for streaming data. 

Data accuracy 

To ensure the accuracy and reliability of your data, you need to consider the order, consistency, and durability of your streaming data. Data that gets out of sequence during processing won’t make sense or be as valuable. The same is true if you’re using stale data or data that has been modified in any way. 

Fault tolerance 

Since data streaming relies on so many separate systems and moving parts, you need to be aware of how a single point of failure within one of the components has the potential to disrupt the entire process. Consider ways to make your system more reliable or redundant so you can continue to stream data of all formats, types, and locations, even if small failures occur.

Security and privacy 

Streaming data contains sensitive information about your business and its customers or clients. You need to be able to protect the integrity and privacy of your data from tampering or unauthorized access as it moves through different systems. Being aware of threats and preventing data breaches is also crucial, as they can significantly impact your finances and reputation.

Latency and data overload

While continuous flows of real-time data offer fresh insights and can help you stay ahead of the competition, the sheer volume of data can be overwhelming. It may be hard to identify the most relevant data or develop meaningful insights without a plan in place ahead of time and the right tools to interpret your data.

Examples and use cases of data streaming

Organizations across industries use data streaming in numerous everyday applications. Here are just a few examples:

E-commerce

E-commerce businesses of all sizes use data streaming platforms to analyze customer data and improve their marketing, sales, and operational strategies in real time. Customer demographics and behavioral data can help your business tailor product recommendations and marketing campaigns to better align with their interests, even if they change over time. 

Data streaming can also be used to design personalized discounts or promotions based on what customers have most recently browsed on your website. Real-time access to data is critical for boosting engagement and converting more prospects into paying customers. 

Many e-commerce companies also use data streaming to monitor and optimize their stock levels in real time. It can help you identify seasonal fluctuations and shifts in the market or consumer demand to proactively manage your inventory. That way, you can avoid being out of stock of popular items or having products you can’t move. Data streaming also enables dynamic pricing, allowing you to adjust pricing to align with inventory levels, consumer demand, or the pricing and promotions of your closest competitors. 

Healthcare

A continuous flow of real-time health data makes applications like telehealth and remote health monitoring possible. Data from various sources, such as a patient’s electronic health record, research information, medical devices, and other wearables, are combined, analyzed, and presented in easy-to-understand visualizations so healthcare providers can track conditions and make informed care decisions without having to be in the same physical location as their patient. 

Data streaming shows current trends and anomalies in health data, too, allowing physicians to detect problems earlier for better health outcomes. It’s extremely useful for monitoring diabetes, heart disease, post-surgical recovery, and other chronic conditions with easily tracked metrics. 

Data streaming also helps you transform your practice from a more traditional, service-centered model to personalized, value-based care. You can use patient data to tailor services or treatment plans based on an individual’s needs or health goals, helping patients become more engaged with their health. And with a secure platform, healthcare organizations never have to worry about compromising patient privacy.

Financial services

Finance companies use streaming data in many applications to improve customer-facing and internal operations. Banks, lenders, and other finance organizations can monitor employee performance and discover insights from real-time data to reduce workflow bottlenecks and improve productivity. 

Streaming platforms can also evaluate customer data, which can help you enhance your product or service offerings to better align with their interests and boost customer retention. Additionally, data streaming is used to help assess risk and speed up the processing of credit card, loan, and mortgage applications. 

You can even use streaming data to prevent fraud in your financial institution. The platforms continuously analyze data and can alert you in real time when trends change or anomalies appear, which may indicate fraudulent transactions and help prevent losses. 

Access to real-time data streams also enables personalized investment portfolios. It uses factors such as a customer’s individual risk tolerance and investment goals, along with insights from current market data, to suggest the most optimal investment and trading opportunities. 

IoT

Internet of Things (IoT) devices are programmed for specific applications and embedded in physical sensors, allowing you to collect and stream real-time data from the source to your cloud or data processing center. They can help you track and optimize labor, machinery, inventory, transportation, and more from any location. 

Retailers and supply chain management companies can use IoT devices to monitor and adjust inventory levels based on changing consumer demand or map out more efficient warehouse layouts. They’re also ideal for managing equipment fleets and practicing predictive maintenance for manufacturers, logistics, and transportation companies. 

You’ll also see IoT data streaming in the health and wellness industry, as they enable remote patient monitoring and help practitioners and patients alike track and manage health conditions. With the number of connected devices currently estimated at 18 billion globally and expected to grow to over 32 billion by 2030, businesses across all industries will rely on data streaming to make the most of this technology. 

Logistics and supply chain

As mentioned above, logistics and supply chain businesses can use connected IoT devices and data to operate more efficiently, but the benefits of data streaming don’t end there. Additionally, these companies can use real-time customer data to see product and input demand and quickly take proactive steps to adapt to any shifts in demand by connecting with other distributors or increasing production, increasing order fulfillment and customer satisfaction. 

You can also use real-time data streaming to track traffic and fleet information to help find the most optimal routes, which in turn can reduce transportation costs and customer wait times. A holistic view of logistic and supply chain data also allows for greater transparency across the company. Data streaming can unlock new, formerly hidden opportunities across financial and operational metrics to become more agile to disruptions and changing markets. 

Choosing the right data streaming platform

To benefit from data streaming, you’ll need to use a powerful analytics platform to ingest and process data. While there are many options to choose from, consider the following elements to find the right platform for your organization:

• Integration capabilities: Top data streaming platforms will easily integrate with all your data sources, such as cloud databases, applications, and tools. This feature allows data to move across all systems and be ingested, processed, and analyzed without coding or any extra steps. 
• Scalability and flexibility: Make sure the platform can handle diverse data formats, rapidly changing data volumes, and high-velocity data without disruption.
• Data processing capabilities: Look for data streaming platforms that offer complex event processing and advanced analytics capabilities like AI, machine learning, or predictive analytics to make the most out of your data.
• Governance and security features: Safeguarding your data’s privacy and integrity is a top priority. Ensure the platform offers strong governance and security features, including access management with multifactor authentication, secure architecture, encryption, auditing, and compliance with HIPAA, SOC 2, GDPR, or other industry standards. 
• Ease of use: Low- and no-code, user-friendly interfaces and drag-and-drop features make it easier for developers and business professionals to use the platform to its full potential. 
• Reliability: Consider features like replication and checkpointing to reduce the risk of losing data or disruptions and ensure data reliability if a failure occurs within your data streaming systems.

Finally, consider your specific use cases, volume of data, existing tech stack, and processing requirements when evaluating data streaming platforms for your business. The top choice for your organization will meet your specific needs and be within your budget. 

Ready to see a streaming data platform in action? Watch a two-minute demo to learn how Domo can help you incorporate real-time data streams into your analytics process.