Analyzing data as it is created or changes? Is that possible? Now it is, with streaming analytics, which monitors and responds to continuously flowing data from connected devices and live data channels like the sensors, machine logs, relational databases, social media feeds, location data sources, and so on. The core differentiator of streaming analytics is the “timeliness of analytics”—it happens now in the present moment of incoming data.
What Does Streaming Analytics Offer to Businesses?
Here are the 6 top business benefits of real-time data analytics:
1. Analysis of data as it is created or changes|
2. Automation of most routine Data Management tasks
3. Enhanced decision support in real time
4. Immediate access to remote data or insights through dashboards
5. Improved business productivity through actionable insights
6. Improved systems requiring few Data Science experts
How Does Streaming Analytics Work? reveals how motion data or event-driven data trigger real-time analytics for instantaneous actions or decisions. This unique characteristic of streaming analytics helps to tackle business problems as they happen—like during a financial transaction failure, a website click, or an assembly-line machine malfunction. The business operator, based on the immediate results of streaming analytics, can think of a corrective action then and there.
The article identifies these seven advantages of streaming analytics: updated KPIs by the second, event-driven triggers or alerts, superfast insights, enhanced risk prevention, identification of hidden opportunities, round-the-clock monitoring of operations, and creation of innovative revenue channels.
Is Streaming Analytics a Game Changer for Digital Businesses?
A Forbes Council Post indicated that the cost of streaming analytics was explosive and in those days, this type of analytics was being used mainly for data integration work. In 2019, only about 25% of businesses were using streaming analytics. The two early adopters of streaming analytics were digital trading platforms and critical control systems. However, the gradual reduction of prices of memory and CPU over the years brought about changes to the cost perception of streaming analytics. Over the years, “real-time systems with in-memory processing” have become affordable, accessible, and acceptable to the ordinary businesses.
Now streaming analytics has evolved into an analytics platform of choice for global organizations. Two unique features of streaming analytics are continuously flowing data from diverse data pipelines, like sensor or transactional data, and the “small chunks of live data” —ready to be analyzed and processed. One popular example of streaming data is stock exchange data analysis in real time.
Today, nearly every business uses streaming data technology to process data in real or near-real time, providing an opportunity to make mission-critical business decisions just when they are needed. Cloud and edge computing together play an important role in facilitating streaming analytics in businesses. According to BMC, 84% of Forbes Global 100 thrive on streaming analytics.
Another Forbes Council Post has indicated that IDC has predicted almost “30% of all data generated by the Year 2025 will be real-time in nature.” Interestingly, Gartner has also predicted that by next year, over 50% of “new business applications” will use real-time data for improved business decisions. These two forecasts signal a new era of event-driven responses in many different sectors like healthcare and weather emergencies.
The ultimate objective of streaming analytics is to enable instantaneous responses to data-driven events taking place in real time. Real-time data is often combined with historical data for more powerful, actionable insights.
A McKinsey guide provides practical advice for navigating the post-pandemic economy where streaming analytics will play a major role in accelerating Data Science activities through the use of centralized analytics platforms and tools. Again, the economical in-memory and CPU solutions have made the availability of such platforms possible.
Streaming Business Intelligence: The Next 10 Years
Streaming business intelligence—the next movement in streaming data analysis—is aimed to empower both technical and nontechnical users to view, analyze, and retrieve actionable insights from streaming data in real time. Streaming BI comes in the age of Data Literacy, where the overriding business goal of enterprises is to make data access and use democratic throughout the organizations.
In this day and age, business users cannot afford to wait for Data Science experts to deliver actionable business solutions and decisions. The capability for making instant decisions means the difference between success and failure.
Organizations in every sector are now using connected devices and face the pressure of “data overloads.” These businesses also realize that unless they tap into the high volumes of data choking practically every data pipeline, they will not be able to reap the benefits of advanced Data Science technologies for newer and better business opportunities. Streaming analytics enable real-time analysis of such high volumes of data for risk or fraud prevention, automated predictive maintenance, event-driven responses, and optimized business processes, and operational transparency.
An important layer of streaming analytics is still the real-time data integration layer. This layer ensures “up-to-the-second” data. With streaming analytics gaining momentum, the future business focus will be on “fast data” and not on big data. Get a better understanding of streaming BI in Introducing Streaming Business Intelligence.
The Future of Streaming Analytics
As global businesses continue to navigate the next normal, a glaring trend is cloud-based streaming analytics as a service. With the meteoric growth of business data and data channels, it is easy to understand why traditional business analytics is going through a renaissance in this decade.
It is not just that the analytics platforms and tools have become more sophisticated, the underlying analytics processes are also going through transformation. With data storage technologies like the data lake, now business analysts can view and analyze historical and streaming data together to generate competitive insights.
A Big Data Made Simple article, talks about the future of streaming analytics in the next 10 years. The digital businesses of today, regardless of sector, are using advanced Data Science technologies and tools to remain competitive.
Data today is a core business “asset” that creates multiple opportunities for growth, development, and profit. Streaming data, as the article suggests, will continue to provide value and reap business benefits for the next decade and beyond.
The data-first culture and the Data Literacy drives in businesses met with roadblocks during the recent pandemic, but the momentum is steadily gathering steam once more. Hopefully, data democratization and Data Literacy initiatives across industries will soon make data-driven insights accessible to the ordinary business user without compromising security.
In conclusion, it’s appropriate to mention that a big advantage of streaming analytics is that KPI dashboard generated from real-time streaming data, which immediately reveals weak functional areas, hidden risks, as well as new opportunities in businesses. Along with that, the real-time analytics help uncover trends and patterns for future preparation.
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