Actionable Insight Through Cloud-Delivered Analytics

Discover how organizations in a range of industries use real-time analytics for smart business decisions

Manager of Portfolio Strategy, IBM
Cloud computing continues to pick up momentum for good reason. Some consider it for overall IT cost-effectiveness, while others are drawn to the potential for reduced capital investment. Still others are looking to solve pressing problems such as a chronic shortage of space in the data center or extended cycles for provisioning resources. The cloud can deliver the following benefits:    
Actionable Insight Through Cloud-Delivered Analytics - sidebar



Sneak Preview

Analytics on the Cloud

Elastic resources: The capability to scale up or down quickly and easily to meet demand
Multiple subscription options: From pay-as-you-go options to hourly or monthly perpetual licenses
Comprehensive access: Self-service deployment of all the IT resources needed


Fit-for-purpose streaming analytics delivered through flexible, cloud-based deployment models allows many organizations to easily tap into data in motion, scale the implementation based on demand, and ingest and analyze massive amounts of data cost-effectively. (For a glimpse at an Insight 2014 session focused on IBM-provided, real-time analytics services, see the sidebar, “Insight 2014 Sneak Preview: Analytics on the Cloud.”)

Attendees at Insight 2014, October 26–30, 2014 at Mandalay Bay in Las Vegas, Nevada, can learn a lot more about cloud-based delivery of streaming data analytics by participating in Session 5789 at the conference. This session focuses on advanced, real-time analytics services delivery provided by IBM, which includes exploration of the three platforms for cloud-delivered, real-time analytics implementations discussed in the mainbar of this article. This session also features a demonstration.Readers who will be at the conference and are considering this session are encouraged to submit their real-time analytics use cases or other areas they’d like to see the session cover. Please provide the details in the comments at the conclusion of the article.


Cloud-based delivery of real-time analytics

Because cloud computing provides access to abundant computing power and easy ways to process large amounts of data, it offers a well-suited deployment model for implementing real-time, cloud-delivered analytics. Cloud-based, real-time analytics provides an efficient tool for making decisions anytime and anywhere. “Analytics everywhere” is a phrase heard with increasing frequency across a range of industries, but what does it mean? Quite simply, analytics everywhere means that big data analytics is about more than just capturing and sifting through all the different kinds of data either produced on the cloud or moved onto the cloud. It’s about turning this data into actionable insight for businesses and consumers while at the same time helping reduce IT cost and complexity (see figure). Common industry use-case examples and benefits of real-time analytics in action

    Real-time analytics implementation   Key benefit
Insurance Sensor data such as temperature, wind, wave height, and so forth can be monitored, and sophisticated, cloud-based analytics resources can be scaled up during the hurricane season instead of incurring the cost for utilizing these resources year round.   Enhance safety for more people living in the paths of potential hurricanes while managing costs
Retail Cloud-based, real-time analytics can be deployed during focused marketing campaigns such as holiday sales, and it can dynamically adjust resources for specific levels of sales traffic. Help reduce costs and improve marketing effectiveness for expected spikes in sales traffic  
Government and law enforcement Cloud resources can be scaled up to increase surveillance monitoring and create social media watch lists during large public events such as concerts or political events to identify criminal activity among the chatter.   Allow proactive resource deployment, fast response times, and well-informed first responders
Automotive Data received from a connected car or other vehicle can be analyzed in real time to initiate actions such as automatically applying brakes, turning on windshield wipers, alerting emergency medical providers, or notifying a dealer about a mechanical problem.   Promote safe driving practices and enhance customer satisfaction and loyalty
Energy and utilities Use cloud computing to increase real-time monitoring and analysis of distribution networks during severe weather conditions such as a drought or polar vortex to optimize load, recommend energy conservation measures, and manage costs. Enhance operational efficiency cost-effectively


Industrial-strength analysis of streaming data

The growth of machine-to-machine (M2M) communication within the Internet of Things has compelled IBM to offer cloud-based, real-time analytics services. For example, North America–based, large-equipment manufacturers typically have data centers located in North America. However, their equipment might be deployed globally. These manufacturers can implement cloud computing to help support new services and M2M applications. Because building a data center in Asia or Latin America would very likely not make financial sense for these organizations, cloud computing in particular offers an efficient alternative for creating a global reach and facilitating worldwide business operations. IBM Research developed IBM® InfoSphere® Streams streaming data analytics that is capable of rapidly ingesting and continuously analyzing massive volumes and varieties of streaming data from thousands of sources.1 Implementing InfoSphere Streams helps organizations improve business insight and decision making, and it enables predictive and cognitive analytics capabilities. The technology can process millions of messages per second, and it can be applied across the following delivery platforms for real-time analytics:

  • Development platform as a service (PaaS): Based on selected cost options, the service dynamically provisions an InfoSphere Streams cluster to provide a virtual network computing (VNC) session that includes InfoSphere Streams development tools—in an instance of InfoSphere Streams Studio—and a sample application.2
  • Geospatial analytics PaaS: The IBM Bluemix™ platform offers geospatial analytics services.3 Real-time geospatial analytics applications such as geofencing, location-based marketing, tracking devices by latitude and longitude, and more enable storing data and analytics results to other services. The Bluemix geospatial service allows organizations to expand the boundaries of their application by leveraging real-time, geospatial analytics to track events and understand when devices enter defined regions. In addition, dynamic dashboards and real-time mapping provide visualizations, and sample applications are available to help jump-start projects.
  • Problem identification and resolution software as a service (SaaS): IBM SmartCloud® real-time log analysis SaaS enables developers and IT operations staff to collect large volumes of structured, semistructured, and unstructured data and transform it through analytics into actionable intelligence for enhanced enterprise IT component performance and optimization.4

Cloud alternatives for rapid analytics in near-real time

The capability to derive actionable insight from analysis of real-time streaming data affords organizations spanning a wide range of industries the benefits of cost-effective big data analytics. This insight allows them to make rapid, well-informed decisions that can quickly yield successful business outcomes, without requiring the up-front cost and additional resources to get on-premises infrastructure in place. IBM provisions key cloud-based services for platforms that offer InfoSphere Streams for VNC sessions, geospatial analytics, and log analytics. Please share any thoughts or questions in the comments. 1 IBM Stream Computing, InfoSphere Platform website. 2 IBM Cloud Marketplace, IBM InfoSphere Streams as a Service trial. 3 IBM Bluemix, geospatial analytics. 4 IBM SmartCloud Analytics, log analysis.  


The Forrester Wave: Big Data Streaming Analytics Platforms, Q3 2014,” by Mike Gualtieri and Rowan Curran, Forrester Research, Doc # 113442, July 2014. “Of Streams and Storms – A Direct Comparison of IBM InfoSphere Streams and Apache Storm in a Real-World Use Case,” IBM Software Group white paper, June 2014.  

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