What is Streaming Analytics?

How Does Stream Analytics Work?

Streaming analytics, also known as event stream processing, is the analysis of huge pools of current and “in-motion” data through the use of continuous queries, called event streams. These streams are triggered by a specific event that happens as a direct result of an action or set of actions, like a financial transaction, equipment failure, a social post or a website click or some other measurable activity. The data can originate from the Internet of Things (IoT), transactions, cloud applications, web interactions, mobile devices, and machine sensors. By using streaming analytics platforms organizations can extract business value from data in motion just like traditional analytics tools would allow them to do with data at rest. Real-time streaming analytics help a range of industries by spotting opportunities and risks.
 
 

The Advantages of Streaming Analytics

• Data visualization. Keeping an eye on the most important company information can help organizations manage their key performance indicators (KPIs) on a daily basis. Streaming data can be monitored in real time allowing companies to know what is occurring at every single moment
• Business insights. In case an out of the ordinary business event occurs, it will first show up in the relevant dashboard. It can be used in cybersecurity, to automate detection and response to the threat itself. This is an area where abnormal behavior should be flagged for investigation right away.
• Increased competitiveness. Businesses looking to gain a competitive advantage can use streaming data to discern trends and set benchmarks faster. This way they can outpace their competitors who are still using the sluggish process of batch analysis.
• Cutting preventable losses. With the help of streaming analytics, we can prevent or at least reduce the damage of incidents like security breaches, manufacturing issues, customer churn, stock exchange meltdowns, and social media crisis.
• Analyzing routine business operations. Streaming analytics offers organizations an opportunity to ingest and obtain an instant insight from the real-time data that is pouring in.

Your company will be able to answer questions like:

• How many customers do you have in your store at this very moment, and what are they most likely to purchase?
• Which vehicles in our fleet are using the most fuel and why?
• Is there a machinery in your factory that could fail in the next five business days, and what spare parts will be required to keep it running?

Your company can now monitor in real time: manufacturing closed-loop control systems; the health of a network or a system; field assets such as trucks, oil rigs, vending machines; and financial transactions such as authentications and validations.

• Finding missed opportunities. The streaming and analyzing of Big Data can help companies to uncover hidden patterns, correlations and other insights. Companies can get answers from it almost immediately being able to upsell, and cross-sell clients based on what the information presents.
• Create new opportunities. The existence of streaming data technology brings the type of predictability that cuts costs, solves problems and grows sales. It has led to the invention of new business models, product innovations, and revenue streams.

Streaming Analytics with Azure Databricks

Additional Resources

• Simplifying Streaming Analytics with Delta Lake and Spark Webinar
• Streaming Analytics with Spark, Kafka, Cassandra, and Akka
• Get High-Performance Streaming Analytics with Azure Databricks