In my last blogs I talked about Big Data, the Internet of Things (IOT) and Data at Rest. As we learned, there are two main types of data that are of interest in a Big Data environment – data at rest and data in motion (or streams).  Data in motion is data that is constantly streaming into the system. The sources for this data are wide ranging and include sensors, social media, geospatial positioning data, facial recognition, video, audio, satellite, devices, and other items that continually create time based data.

If your company struggles with the ability to analyze and act upon rapidly changing data in motion, cannot keep up with the sheer velocity of the data and does not have the ability to use predictive analytics to grab at opportunities that data may present, then it is time to consider a data in motion or streaming analytics solution.

Understanding Streaming Data

Streaming data is about volume and velocity – enormous amounts of data flowing into the system that need to be put into some context so that the data can be used in a more meaningful manner. By adding context to these masses of data the company is better able to:

• gain real-time actionable insight
• determine where best to focus their workers
• determine where to focus the company itself
• detect emerging patterns
• make decisions based on the insight and patterns

When looking at context aware systems there are several things to look for. Some of the terminology you will see includes:

• Sequence-neutral at scale
  • The ability to make sense of all data, with no particular ordering or sequence required.
• Context accumulation
  • The ability to make sense of all data without having to define new rules or train the system. It allows you to take advantage of self-learning, self-correcting, cognitive systems.
• Real-world ready
  • The ability to make sense of all data across space, geography, time, language and culture.
• Privacy by design
  • The ability to make sense of all data while preserving identities and keeping sensitive data secure.
• Managed uncertainty
  • The ability to make sense of all data without the need to cleanse or govern it, so all data can be used to develop the right context.

Data in motion with context awareness is extremely valuable in many industries, but particularly so in healthcare. The ability to see a change in a patient’s sensor reading and to then put that in context with their known conditions and medications as well as information on the local area breakouts of illnesses or allergen information is incredibly valuable and can be the difference between life and death for some people. It also helps reduce expenses both for the hospital and the patient as treatment can be much faster and more proactive. Another key point is that timeliness is also critical. Streaming data typically loses value over time so it is important to try to analyze and act on that data as quickly as possible. Without that it is possible to lose opportunities you never knew existed.

About IBM Infosphere Streams

IBM Infosphere Streams is used to analyze streaming data in real time and to apply context. It is a highly scalable and flexible analytics platform specifically targeted at data in motion. It continuously integrates and analyzes data in motion so that it is possible to dynamically make business adjustments such as:

• fostering more dynamic, personalized customer interactions
• combating security risks
• enhancing operational efficiencies
• improving service levels

IBM Infosphere Streams first shipped in 2009 and is the system that enables the development and execution of applications that process information in data streams. The platform allows continuous and fast analysis of very large volumes of moving data to help improve the speed of business insight and decision-making. It consists of a proprietary programming language, an Eclipse-based integrated development environment (IDE) for applications, and a runtime system that can execute the applications on a single or distributed set of hosts. Additionally, the Streams Studio IDE includes tools for authoring and creating visual representations of the InfoSphere Streams Applications. IBM has also added integration with Datawatch visualization software to provide front-end visualization of results.

IBM Infosphere Streams Features:

• Analysis of data in motion
  • Allows for rapid minimal effort decision making
• Deploy a high performance, scalable analytic runtime
  • Reduces hardware requirements by up to 90% over existing traditional technologies
• Analyze traditional and non-traditional data types
  • Allows you to make informed and insightful decisions
• Reuse of PMML mining/ scoring models and existing C++/Java code
  • Provides a faster time to value and lower development costs
• Develop applications in Java or IBM Streams Processing Language
  • Reduces the learning curve and provides better time to value
• Integrate with open source technology such as Apache Spark
  • Lets you build more intelligent applications and take advantage of what is already available
• Integrate with data governance
  • Lets you gain more confidence in the data stream insights

Free Trial

If you want to try IBM Infosphere Streams, there is a free to download version called IBM Infosphere Streams Quick Start Edition. This is a full featured edition but it has no support except from the communities and forums. If you decide you want to use it permanently in production, then you upgrade to the full version which includes support.

Summary

Without context, data is just a bunch of bits that have no real meaning.  Providing context to data in real time adds a vital layer of value that lets you make timely insights that can be justified and trusted. This type of analysis allows for rapid detection of new and emerging patterns that help the company be more proactive and thus, more competitive.

Data streams are the new normal and businesses are now being expected to be more proactive and more dynamic. Stream computing provides the ability for companies to respond to rapidly changing market conditions which provides for incredible business value. If you don’t already have a solution for dealing with data in motion then it is time to consider ways that a solution like Infosphere Streams might help make your business more competitive and more efficient.

References

IBM Infosphere Streams

IBM Infosphere Streams Quick Start Edition

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Schedule a consultation today to learn how Flagship can make the most of your data in motion.

If you liked this blog, you also might like:  Data at Rest Will Remain at Rest, Unless Acted Upon by an Outside Force

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