Streaming Analytics: What It Is and How it Benefits Your Business
What is Streaming Analytics?
Streaming analytics platforms can ingest, analyze, and act on real-time streaming data coming from various sources so you can take immediate action while the events are still happening. It has the ability to gather and analyze large volumes of data arriving in “streams” from always-on sources such as sensor data, telematics data, machine logs, social media feed, change data capture data from traditional and relationship databases, location data, and so on.
How is Streaming Analytics Different from Traditional Data Analytics?
The difference between streaming analytics and traditional analytics lies in when data gets analyzed. Traditional analytics follows a store-first-then-analyze-paradigm, where we first store the data and then analyze it for deriving insights. Traditional analytics is also mainly applied to data at rest. In streaming analytics, we analyze the data first, while the events are still happening, and then store the relevant data for batch analysis. This allows streaming analytics platforms to handle the scale and constant flow of information and deliver continuous insights to users across the organization.
the Benefits of Streaming Analytics?
The top benefits of streaming analytics are:
- Improve operational efficiencies
- Reduce infrastructure cost
- Provide faster insights and actions
Organizations in every industry have data streaming
available from applications, social media, sensors, devices, websites, and more
Essentially, streaming analytics is all about extracting business value from data in motion in the same way traditional analytics tools make use of data at rest. Organizations in every industry have data streaming available from applications, social media, sensors, devices, websites, and more sources; they need flexible, scalable tools and processes to make it accessible and useable at the moment it’s needed.
For example, real-time streaming analytics can help a
company issue alerts instantly when a customer’s experience is degraded, or
when fraud is detected. The customer gets a better response and service
experience, and the company can act before a small outage or incident grows
into a broader, more serious situation that may cost more time and money to
resolve and harm their reputation.
Additionally, information derived from real-time analytics can be used to identify anomalies and business changes (such as a sudden spike in demand for a product or service, or a defect in manufacturing) as they occur. Such information allows companies to take instant action and seize an opportunity that they otherwise might miss.
What Are Some Examples of Real-World Streaming Analytics Use Cases?
Use cases of real-time analytics performed on streaming data can be found in cybersecurity, financial services, retail, manufacturing, the energy industry, healthcare, and many other industries. Here are a few examples:
- Manufacturing: Many manufacturers embed intelligent sensors in devices throughout their production line and supply chain. Analyzing the data from these sensors in real-time allows a manufacturer to spot problems and correct them before a product leaves the production line. This improves production and efficiency of operations—and saves money. For more on Industrial IoT and IoT data management, read our reference article.
- Cybersecurity: In cybersecurity uses, streaming analytics can instantly identify anomalous behavior and suspicious activities and flag them for immediate investigation. So, rather than remediating after a problem occurs, the attack is stopped before it can do any damage.
- Hospitality: A hotel chain might use streaming analytics to monitor reservations in real-time. Spotting a location that has high availability in the late afternoon, the chain could text or email special promotions to frequent guests in that area to fill those empty rooms that night.
Want to learn more about streaming analytics and how it can benefit your business? Watch our on-demand webinar, “Next-Gen Customer Experience with Real-Time Streaming Analytics and IoT,” or check out our demo of Data Engineering Streaming 10.4.