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9 Digital Business Transformation Predictions for 2016

Blog: The Tibco Blog

2015 was a year of tremendous change in the software industry. Driving the rapid pace of business throughout the year were the rise of digital infrastructure, analytics, and the cloud. What the industry calls “the digital transformation” enables organizations to capitalize on advanced communications—and data-reliant technologies; for example, enhancing the customer experience or optimizing knowledge worker productivity through tool integration.

TIBCO knows the business advantages that come from being a digital enterprise. Our approach for serving organizations in the midst of “digitalization” involves deploying what we call the Fast Data platform. This platform is comprised of integration to allow users to connect and engage in useful and intuitive ways, analytics to supply users with the right business intelligence to make critical decisions at the right time, and event processing to enable users to assess both real-time and historical data at any scale for informed and decisive action.

Looking ahead to 2016, enterprises will continue to invest in digital transformation with event processing, integration, and analytics technologies. Mark Palmer, SVP of integration and event processing, Michael O’Connell, chief analytics officer, and Randy Menon, VP of product management, strategy and user experience join together to bring nine predictions of what you’ll see more of in the coming year.


The move to the cloud is expediting enterprise innovation across the board, providing scalable on-demand data resources, and fostering organizational speed and agility. The logical next step is to improve the connection and integration of cloud technology with the existing products and services that businesses have built their foundations upon.

1. Platform-as-a-Service (PaaS) is increasingly deployed by serious enterprises. Mainstream companies will bet big on cloud development platforms such as Cloud Foundry, Docker, and the like for their most mission-critical applications. This will, in turn, raise requirements for cloud-first architectures and tool packaging.

2. APIs will be prolific in the mainstream. As companies move towards even broader use of Software-as-a-Service (SaaS) apps to complement or replace enterprise applications, and as mobile apps continue to multiply, the need for APIs that feed cloud connectivity will grow, with increased emphasis on better developer tools.

 3. Application development teams will drive enterprise buying behavior. Application development teams will start to drive a higher degree of buying behavior, which will spur drastic improvements in tool packaging and wider consumption of integration solutions.


The future of analytics is incredibly bright. Anticipated refinement lies in a combination of continually improving methods to collect the most data from the best sources and transform it in to useable information conveyed in clearer and more actionable ways.

4. Visualization turns insights into action. The “what-if” and “action” part of the analytics equation will be getting some much-needed attention. Highly configurable dashboards will drive greater insight, delivering targeted visual scenarios to end users and imparting richer understanding. By enabling ad-hoc analysis and visual “popping” of existing and potential scenarios, businesses will be able to pull more accurate insights from disparate data sources. And, by enabling simple configuration of alert thresholds, end users will be pushed insights via notifications and contextual analyses for rapid action.

 5. Better predictive customer analytics will become more ubiquitous. Through the improved analytic segmentation of customers, propensity to buy a product or service, and affinity for related products, companies can provide real-time contextual offers that apply directly to individual consumers. These personalized, granular insights will allow for increased awareness of customer expectations (or machine conditions), and facilitate more responsive and targeted intervention.

 6. Industrial real-time analytics will become more pervasive. The insights gained from better visual, predictive, and prescriptive analytics will make a big impact on real-time industrial and Internet of Things (IoT) equipment, as well as customer engagement channels. From machine malfunction alerts to driving customer actions, these advanced analytics functions will give businesses incredible real-time engagement, intervention, and measurement capabilities.

Event Processing

In spite of what seems like an endless hype cycle, the Internet of Things is no longer knocking— it has kicked down the door and is now screaming for attention. As standards begin to congeal around connected devices, products will become even further integrated into everyday activities. The same can be said for the event processing capabilities that (in conjunction with analytics) are increasingly essential to industry.

 7. The Internet of Things will go mainstream in business. Companies will start to see significant ROI from IoT deployments, as consensus around IoT standards will finally emerge. This will encourage fast and widespread adoption of IoT implementations across enterprises.

 8. Event processing and analytics are more frequently used together. In order to make data-driven insights derived from analytics tools actionable, there will be an increasingly tighter integration between event processing and analytics technologies and tools.

 9. Spark will ascend as the Fast Data repository for data at rest. Spark will usurp Hadoop as the go-to open source data framework for processing data at rest for event processing applications. Streaming analytics and complex event processing (CEP) benefit from the in-memory processing of Spark. As event processing gains stature within the enterprise, so too will Spark.

So that’s what we predict will be huge in integration, analytics, and event processing in 2016. Post on social media at #2016Next to weigh in on what you think will happen in the coming 12 months to advance digital transformation.

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