We live in a data rich world. By 2020, it is predicted that there will be 30 billion devices in use by IoT applications, up from 15 billion devices today. Data from these devices and from growing digital transactions is a valuable commodity in the digital economy. This data is quickly becoming overly complex for traditional analytics tools, leaving businesses with abundant data but without the systems to help them gain valuable insights.
In traditional systems, a standard dataflow might look like this: the system generates data; that data produces an insight; that insight inspires an action. The more latency between these steps, the more customer satisfaction decreases, the lower your ROI, and the longer it takes your organization to move forward.
When we architected SAP HANA, we knew it was absolutely critical to reduce these latencies by bringing the necessary processing and computation into a single environment. This means SAP HANA works directly with the data the application or transaction generates. Using technologies such as Smart Data Integration and Smart Data Access, SAP HANA can connect to data anywhere on the data highway and bring that data into the SAP HANA data platform.
Once the data is in the SAP HANA data platform, it is turned into insight using a full set of intelligent and machine learning algorithms, such as cluster analysis, regression analytics, and more. A large proportion of enterprise data contain some form of location information, and important relationships among these entities are often completely hidden. With SAP HANA’s built-in engines for geospatial computing, for graph processing, for text search, all of this information can be turned into insight. And all the data is kept together for complete consistency and security.