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New cloud-based systems like SAP HANA take advantage of particular hardware and IT architecture setups to utilize the data and also exploit the power of machine learning or artificial intelligence to crunch that data and provide results.
SAP calls HANA an “in-memory system” – that means it holds certain kinds of data in the hardware’s RAM, rather than putting it into disk areas for storage. This enables client businesses to get much quicker access to the data – practically speaking, to get it in real time.
Why is this important? Businesses are using SAP HANA in many different kinds of ways, and adding on a multitude of different kinds of tools to get real-time business intelligence. However, the general idea is that HANA provides the platform for intaking the data, and sophisticated machine learning tools sort and classify that data to return the smart results that businesses need to make decisions.
You can see this with enormous retailers like Wal-Mart – which uses HANA to process transaction records for thousands of stores in real time. Other companies may use HANA to look at data that comes in from financial transactions, or to monitor manufacturing setups. Smart manufacturing is a major use for HANA and other systems that provide real-time data – in combination with machine learning algorithms that help the human support personnel make sense of the data. For example, sophisticated tools tied into a real-time HANA platform can show managers whether a specific part of a production line is slowing down, and why. These tools can point to bottlenecks and failures in a complicated system, so that companies keep their lines up and running for maximum productivity and efficiency.
Another major area of HANA usage is in sales. Cisco is one of the top leading IT companies in the world. A fact sheet from the company shows how business leaders use HANA to work with floods of sales information including order numbers, sales forecasts and information about the sales pipeline. Cisco’s internal platform, which is called Dynamic Insights for Sales Executives (DISE) runs on HANA, which the company calls the “analytical engine” for in-memory computing.
Companies can set up these sorts of proprietary tools on the HANA platform according to their needs. A smaller business may only process very specific kinds of data to figure out how to serve customers or improve productivity. Larger and more established companies may have multichannel setups to look at things like marketing, sales and manufacturing through different lenses. Regardless, what companies are doing is taking advantage of the engineering of an in-memory or resident memory system to glean the results from machine learning setups faster, which can lead to better agile decision-making and development.
