The world is running faster. Our use of computer systems has given us the possibility, the power, and the need to process information with a far higher degree of immediacy. This immediacy has given rise to the term “real time.”

We use real time to denote seemingly instantaneous technology and use the label itself to describe real-time computing, real-time analytics, real-time encryption, and real-time control systems—all of which may use real-time transport protocols and live inside real-time operating systems.

But What Does “Real” Really Mean?

Here’s the spoiler alert: There is no such thing as real time, because real-world real time moves way too fast for any computer. I know time is simply a relative concept, but you get the point.

James Martin summed up what real-time computing means in his 1965 book Programming Real-time Computer Systems. He wrote, “A real-time system controls an environment by receiving data, processing [it], and returning the results sufficiently quickly to affect the environment at that time.”

So, real time is just fast enough for us to perceive computer processing to have been immediate within the context of the job at hand. Why all the clarification and explanation? Because as ASUG members will likely be aware, SAP HANA has been built to execute data analytics jobs in real time.

How HANA Hustles

SAP HANA achieves its real-time immediacy using in-memory computing. This allows it to process data (analyzed, integrated, computed upon, stored, etc.) in RAM memory rather than having to perform read/write functions on and off physical hard disks, which would consume valuable input/output time.

If you’re still asking why real-time analytics in the context of SAP HANA is important, it is because SAP HANA allows organizations to run more ad hoc queries on their business data—and fast ad hoc queries lead to real-time data analytics.

So, real time is all about speed, but it’s also about agility.

And Now, Real-Time Responsibility

With the power of real-time data analytics comes a greater responsibility for data quality. Organizations will need to feed SAP HANA relevant, cleansed, and accurate data if they want to get the right kind of results, in real time or anytime after that.

This is because SAP HANA can perform data analytics on source data rather than having to go through an extract, transform, load (ETL) process.

ASUG members will need to think about source data quality alongside data governance and compliance issues if they want to get the right real-time data analytics outputs.

Enter SAP Data Services

SAP provides a solution in the form of SAP Data Services, which is enterprise-level data management software that can integrate, transform, and improve your data and make it available for real-time analytics and processing.

Related products in this category include SAP Agile Data Preparation, SAP Data Quality Management, SAP Information Steward, and SAP Master Data Governance. For all our talk of SAP HANA and the supporting services, SAP provides a key access point to real-time analytics through SAP Analytics Cloud.

Real-World Applications

SAP points to customer examples including Hoerbiger Holding AG, a Swiss industrial machinery and components business.

Hoerbiger is using real-time data analytics to analyze plant data and monitor service excellence in parts. The company established a reporting system for its plants with globally defined KPIs to improve plant performance by creating cloud-based business dashboards that pull data from the ERP without storing it in the cloud. Ultimately, Hoerbiger was able to shorten audit times and reduce the support efforts in IT to free staff to work on more-strategic tasks.

More and more businesses are using real-time data analytics and looking for use cases where they can apply this technology. Other industries likely to benefit from this technology include finance and medicine.

How Data Has Reinvented Finance

Looking more closely at finance: Banks are using real-time data analytics to crunch through traditional (money market) data and now incorporate that with nontraditional (consumer trends, world news, or weather) data to create a wider view of the way any stock or share is about to swing.

Also in finance, real-time data analytics is now a fundamental function used to underpin the Markov models used to identify anomalies that can help to pinpoint fraudulent activities.

Closer to your own wallet, banks and financial institutions are using real-time data to analyze the exabytes-worth of transactional data that users are currently generating in order to offer new services designed to increase customer loyalty.

Data as the Cure?

Looking at medicine, we know that batched data is useful to provide us with analytics focused on long-term trends (e.g., shifts in mortality rates for entire country populations and so on). But real-time data analytics is needed to connect smart wearables to centralized patient management systems.

Real-time healthcare data and the use of electronic medical records can lead to actions in minutes, if not seconds.

Where we could go next is to fuse different data sources together (batched, historical, clinical trial, wearable readouts, etc.) and tie those streams with patients’ physiological vital signs, electrocardiogram (ECG), heart rate monitors, and respiratory devices. As these devices become more interconnected and the critical data sounds the appropriate alarms as needed, the future could be a healthier place.

The Real-Time Road Ahead

The future for real-time data analytics is positive, but with caveats. New business models will have to be developed. A deeper responsibility for data quality and governance arises. Organizations will need to create “human guard rails” to prevent real-time mistakes from occurring as these new systems emerge.

Technology analyst firm Forrester estimates that IT departments could save as much as 37 percent on their operational costs if they used real-time data analytics prudently.

The real goal for ASUG members to think about is how they will now generate a culture based around what we might call “decision management.” Not data management or business process management. (I’ll assume you already have those functions in place.) We’re talking about decision management, where we now look closely at the way real-time analytics could change the course of live businesses every day. Real-time information paves the path away from reactive and toward proactive decision-making.

If you’re looking to learn how your peers are doing more with business intelligence and analytics, read more in our Insights.