Harnessing the Data Explosion
Data volumes are growing exponentially, from not just human-generated but now also machine-generated sources. Digital touchpoints are proliferating rapidly driven by new devices and the internet of things (IoT). The ability to connect to any and all data from any device or touchpoint and to harness this data for business benefit is the new frontier for competitive advantage. Organizations that are able to make sense of data and use it to derive new business insights and to act on those insights, often without human intervention, will be the ones to survive and thrive in tomorrow’s world. In this big data environment where everything must be connected, development organizations require a new way to build applications that can harness the power of all data, whether it is from systems of record, IoT or any other data source. And they require a more modern and flexible means of constructing applications based on microservices.
"Those organizations whose developers effectively use machine learning and deliver cognitive applications will gain a significant advantage over competitors, ensuring their place as the industry leaders of tomorrow."
– Al Gillen, Group Vice President, Software Development and Open Source, IDC
What’s Needed: A New Cognitive-First Development Platform
In short, what’s needed is a new application development and deployment platform. One which empowers virtually any organization to build cognitive applications—applications built on a platform that supports predictive results using machine learning, then leverages those results for business value. These applications must connect to and consume all kinds of data from every endpoint and system, and provide for smart user interactions in all types of interfaces from web and mobile to chatbots, voice, virtual reality, tactile interfaces and more.
The Challenges of Building Cognitive Apps
But building these machine learning-powered cognitive apps today is time and labor intensive. It requires complex connections to operational and transactional data, the management of real-time streaming of IoT data, and the incorporation of predictive analytics and machine learning to reap the true rewards of big data analytics. These tasks typically require the hiring of hundreds of data scientists—a viable solution for only the largest global companies. In addition, time to market is critical for these applications—organizations are finding they can’t build them fast enough, and they can’t keep up with business demand.
The Solution: Democratized Machine Learning
What is required is a new way to build multi-channel intelligent applications, where time to market is rapid, and resource requirements are minimal. A platform that democratizes machine learning, and combines it with the most modern application development approach, will enable organizations of all sizes to drive competitive advantage through smarter applications.
With a rich heritage of technology driving hundreds of thousands of mission-critical applications, Progress is well-positioned to deliver on the promise of cognitive-first applications.
Modern Back End
Progress provides back-end services to support the deployment of flexible applications, including, security, integration and messaging for mobile applications and more. A microservices approach will support new workloads, including IoT and streaming data use cases providing a single back end as a service (BaaS) for all application types.