Turning Data into insights with IBM Streams
IBM® Streams is a software platform that enables the development and execution of applications that process information in data streams. IBM Streams enables continuous and fast analysis of massive volumes of moving data to help improve the speed of business insight and decision making.
IBM Streams is an advanced analytics platform that allows user developed applications to quickly ingest, analyze and correlate information as it arrives from thousands of data stream sources. The solution can handle very high data throughput rates and helps to:
- Analyze data in motion – Provides sub-millisecond response times allowing you to view information and events as they unfold;
- Simplify development of streaming application – use integrated development environment;
- Extend the value of existing systems – Integrate with current applications, and support both structured and unstructured date sources;
Why is IBM Streams relevant for today’s business models?
There is no doubt that businesses today realise the importance of data and the need to not only the way it is gathered, but more importantly they have to try to leverage this huge asset and look at ways to extract the value inherent therein. Data is only useful if actionable insights can be generated from it in a timely manner to help the business deliver faster and more cost effectively. In today’s business models this data is generated through numerous ways, collected and aggregated heterogeneously and IBM Streams will help enhance the day to day system management in the following areas:
- Unstructured Data: IBM Streams is able to provide a platform that can handle virtually any data whether structured or unstructured. It supports non-stop data such as texts, audio, images, voice, video, web traffic, GPS data, email, financial transactions, satellite data and sensor logs.
- Big Data: The amount of data being created continues to grow in terms of volume, variety and velocity. IBM Streams ability to handle large volumes of data (millions of messages or events) per second makes it ideal for many business models of today. Its ability to integrate with other data infrastructure like Hadoop, Spark and others makes it really relevant in today’s business models. It helps reduce data storage by simple filtering and extracting only relevant information that is needed by the business. It can analyse terabytes of data per second/ petabytes per day
- Real Time: Real Time Analytics Processing (RTAP) allows the ability to have current fact finding – knowing immediately what is happening e.g. advertising impact during a live football match. IBM Streams has tremendous processing and large data handling and analytics capabilities enabling insights to be generated and delivered in real time as this is crucial to current business models in dealing with customers today. Customers now require insights now and cannot wait. IBM Streams allows real time analytics as data can be acquired, analyzed and acted on in real time. It can be used to detected / predict e.g. Potential fraud (credit card) and prevent it. Facial detections can be delivered in real time and even customer service initiatives through voice to text and sensors delivering critical insights about a potential customer about to defect. Network intrusion can also be anticipated, detected and prevented.
- Deep Learning: IBM Streams can be integrated with several business solutions and offers built in analytics like machine learning, natural language, spatial-temporal, text and acoustic to create adaptive streams applications. Deep learning is a subset of machine learning. See illustration on next slide.
Cloud Computing: Most of today’s models mean that businesses don’t really want to manage the technology related to managing the data and storage related to it. They simply want the interface and access to the data. They are not concerned about the storage, location or how the data is processed. They want the results on the device of their choice. IBM Streams is cloud based making it relevant in today’s business models as this allows it to be scalable, resources to be shared and insights to be readily available. It offers a Platform as a Service solution giving todays businesses an opportunity to manage applications and data and increasing speed to delivery / setup. This gives it tremendous capability in terms of scalability as well.
IBM Streams is clearly relevant for today’s new business models as it provides the capability to ingest data from many sources be, they structured or unstructured, index, classify and make it accessible in line with the stipulated governance framework in real time. Its ability to integrate with many other applications makes it possible to scale and increases its relevance as it will also integrate with IoT and many AI powered initiatives.
